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McGinnis KA, Justice AC, Marconi VC, Rodriguez-Barradas MC, Hauser RG, Oursler KK, Brown ST, Bryant KJ, Tate JP. Combining Charlson comorbidity and VACS indices improves prognostic accuracy for all-cause mortality for patients with and without HIV in the Veterans Health Administration. Front Med (Lausanne) 2024; 10:1342466. [PMID: 38356736 PMCID: PMC10864663 DOI: 10.3389/fmed.2023.1342466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 12/31/2023] [Indexed: 02/16/2024] Open
Abstract
Introduction As people age with HIV (PWH), many comorbid diseases are more common than among age matched comparators without HIV (PWoH). While the Veterans Aging Cohort (VACS) Index 2.0 accurately predicts mortality in PWH using age and clinical biomarkers, the only included comorbidity is hepatitis C. We asked whether adding comorbid disease groupings from the Charlson Comorbidity Index (CCI) improves the accuracy of VACS Index. Methods To maximize our ability to model mortality among older age groups, we began with PWoH in Veterans Health Administration (VA) from 2007-2017, divided into development and validation samples. Baseline predictors included age, and components of CCI and VACS Index (excluding CD4 count and HIV RNA). Patients were followed until December 31, 2021. We used Cox models to develop the VACS-CCI score and estimated mortality using a parametric (gamma) survival model. We compared accuracy using C-statistics and calibration curves in validation overall and within subgroups (gender, age ≥65 years, race/ethnicity, and CCI score). We then applied VACS-CCI in PWH and compared its accuracy to age, VACS Index 2.0, CCI and VACS-CCI with CD4 and HIV RNA added. Results The analytic sample consisted of 6,588,688 PWoH and 30,539 PWH. Among PWoH/PWH, median age was 65/55 years; 6%/3% were women; 15%/48% were Black and 5%/7% Hispanic. VACS-CCI provided the best discrimination (C-statistic = 0.81) with excellent calibration (predicted and observed mortality largely overlapped) overall and within subgroups. When VACS-CCI was applied to PWH it demonstrated similar discrimination as VACS Index 2.0 (C-statistic = 0.77 for both) but superior calibration among those with CD4 < 200. Discrimination was improved when CD4 and HIV RNA were added VACS-CCI (C-statistic = 0.79). Liver and kidney disease, congestive heart failure, malignancy, and dementia were negatively associated with CD4 (p-trends all <0.0001). Discussion Among PWH and PWoH in VA care, age alone weakly discriminates risk of mortality. VACS Index 2.0, CCI, and VACS-CCI all provide better discrimination, but VACS-CCI is more consistently calibrated. The association of comorbid diseases with lower CD4 underscores the likely role of HIV in non-AIDS conditions. Future work will include adding CD4 and HIV RNA to VACS-CCI and validating it in independent data.
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Affiliation(s)
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, CT, United States
- Yale School of Medicine, New Haven, CT, United States
| | - Vincent C. Marconi
- The Atlanta Veterans Affairs Medical Center, Emory University School of Medicine and Rollins School of Public Health, Atlanta, GA, United States
- VA Medical Center, Decatur, GA, United States
| | - Maria C. Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Ronald G. Hauser
- VA Connecticut Healthcare System, West Haven, CT, United States
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, United States
| | - Krisann K. Oursler
- Department of Internal Medicine, Virginia Tech Carilion School of Medicine, Roanoke, VA, United States
- VA Salem Healthcare System, Salem, VA, United States
| | | | - Kendall J. Bryant
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United States
| | - Janet P. Tate
- VA Connecticut Healthcare System, West Haven, CT, United States
- Yale School of Medicine, New Haven, CT, United States
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Justice AC, Tate JP, Howland F, Gaziano JM, Kelley MJ, McMahon B, Haiman C, Wadia R, Madduri R, Danciu I, Leppert JT, Leapman MS, Thurtle D, Gnanapragasam VJ. Adaption and National Validation of a Tool for Predicting Mortality from Other Causes Among Men with Nonmetastatic Prostate Cancer. Eur Urol Oncol 2024:S2588-9311(23)00289-4. [PMID: 38171965 DOI: 10.1016/j.euo.2023.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 10/24/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer. OBJECTIVE To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM). DESIGN, SETTING, AND PARTICIPANTS An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups. RESULTS AND LIMITATIONS Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application. CONCLUSIONS VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation. PATIENT SUMMARY Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality.
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Affiliation(s)
- Amy C Justice
- VA Connecticut Healthcare, West Haven, CT, USA; Pain Research, Informatics, Multimorbidities, Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA; School of Public Health, Yale University, New Haven, CT, USA.
| | - Janet P Tate
- VA Connecticut Healthcare, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Frank Howland
- Wabash College Economics Department, Crawfordsville, IN, USA
| | | | - Michael J Kelley
- Durham VA Health Care System, Durham, NC, USA; Cancer Institute and Department of Medicine, Duke University, Durham, NC, USA
| | | | - Christopher Haiman
- Center for Genetic Epidemiology, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Roxanne Wadia
- Department of Anatomic Pathology and Lab Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Ravi Madduri
- Data Science Learning Division, Argonne Research Library, Lemont, IL, USA
| | - Ioana Danciu
- Oak Ridge National Laboratory, Oak Ridge, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John T Leppert
- Department of Urology, Stanford University, Stanford, CA, USA; VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Michael S Leapman
- VA Connecticut Healthcare, West Haven, CT, USA; Department of Urology, Yale School of Medicine, New Haven, CT, USA
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3
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Weinstein EJ, Stephens-Shields AJ, Newcomb CW, Silibovsky R, Nelson CL, O'Donnell JA, Glaser LJ, Hsieh E, Hanberg JS, Tate JP, Akgün KM, King JT, Lo Re V. Incidence, Microbiological Studies, and Factors Associated With Prosthetic Joint Infection After Total Knee Arthroplasty. JAMA Netw Open 2023; 6:e2340457. [PMID: 37906194 PMCID: PMC10618849 DOI: 10.1001/jamanetworkopen.2023.40457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 09/18/2023] [Indexed: 11/02/2023] Open
Abstract
Importance Despite the frequency of total knee arthroplasty (TKA) and clinical implications of prosthetic joint infections (PJIs), knowledge gaps remain concerning the incidence, microbiological study results, and factors associated with these infections. Objectives To identify the incidence rates, organisms isolated from microbiological studies, and patient and surgical factors of PJI occurring early, delayed, and late after primary TKA. Design, Setting, and Participants This cohort study obtained data from the US Department of Veterans Affairs (VA) Corporate Data Warehouse on patients who underwent elective primary TKA in the VA system between October 1, 1999, and September 30, 2019, and had at least 1 year of care in the VA prior to TKA. Patients who met these criteria were included in the overall cohort, and patients with linked Veterans Affairs Surgical Quality Improvement Program (VASQIP) data composed the VASQIP cohort. Data were analyzed between December 9, 2021, and September 18, 2023. Exposures Primary TKA as well as demographic, clinical, and perioperative factors. Main Outcomes and Measures Incident hospitalization with early, delayed, or late PJI. Incidence rate (events per 10 000 person-months) was measured in 3 postoperative periods: early (≤3 months), delayed (between >3 and ≤12 months), and late (>12 months). Unadjusted Poisson regression was used to estimate incidence rate ratios (IRRs) with 95% CIs of early and delayed PJI compared with late PJI. The frequency of organisms isolated from synovial or operative tissue culture results of PJIs during each postoperative period was identified. A piecewise exponential parametric survival model was used to estimate IRRs with 95% CIs associated with demographic and clinical factors in each postoperative period. Results The 79 367 patients (median (IQR) age of 65 (60-71) years) in the overall cohort who underwent primary TKA included 75 274 males (94.8%). A total of 1599 PJIs (2.0%) were identified. The incidence rate of PJI was higher in the early (26.8 [95% CI, 24.8-29.0] events per 10 000 person-months; IRR, 20.7 [95% CI, 18.5-23.1]) and delayed periods (5.4 [95% CI, 4.9-6.0] events per 10 000 person-months; IRR, 4.2 [95% CI, 3.7-4.8]) vs the late postoperative period (1.3 events per 10 000 person-months). Staphylococcus aureus was the most common organism isolated overall (489 [33.2%]); however, gram-negative infections were isolated in 15.4% (86) of early PJIs. In multivariable analyses, hepatitis C virus infection, peripheral artery disease, and autoimmune inflammatory arthritis were associated with PJI across all postoperative periods. Diabetes, chronic kidney disease, and obesity (body mass index of ≥30) were not associated factors. Other period-specific factors were identified. Conclusions and Relevance This cohort study found that incidence rates of PJIs were higher in the early and delayed vs late post-TKA period; there were differences in microbiological cultures and factors associated with each postoperative period. These findings have implications for postoperative antibiotic use, stratification of PJI risk according to postoperative time, and PJI risk factor modification.
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Affiliation(s)
- Erica J Weinstein
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Alisa J Stephens-Shields
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Craig W Newcomb
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Randi Silibovsky
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Charles L Nelson
- Department of Orthopedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Judith A O'Donnell
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Laurel J Glaser
- Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Evelyn Hsieh
- Veterans Affairs (VA) Connecticut Health System, West Haven
- Section of Rheumatology, Allergy and Immunology, Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Jennifer S Hanberg
- Veterans Affairs (VA) Connecticut Health System, West Haven
- Department of Medicine, Massachusetts General Hospital, Boston
| | - Janet P Tate
- Veterans Affairs (VA) Connecticut Health System, West Haven
- Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Kathleen M Akgün
- Section of Pulmonary, Critical Care, and Sleep Medicine, VA Connecticut Health System, West Haven
- Section of Pulmonary, Critical Care, and Sleep Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Joseph T King
- Veterans Affairs (VA) Connecticut Health System, West Haven
- Department of Neurosurgery, Yale University School of Medicine, New Haven, Connecticut
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Center for Real-World Effectiveness and Safety of Therapeutics, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Cartwright EJ, Pierret C, Minassian C, Esserman DA, Tate JP, Goetz MB, Bhattacharya D, Fiellin DA, Justice AC, Lo Re V, Rentsch CT. Alcohol Use and Sustained Virologic Response to Hepatitis C Virus Direct-Acting Antiviral Therapy. JAMA Netw Open 2023; 6:e2335715. [PMID: 37751206 PMCID: PMC10523171 DOI: 10.1001/jamanetworkopen.2023.35715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 08/21/2023] [Indexed: 09/27/2023] Open
Abstract
Importance Some payers and clinicians require alcohol abstinence to receive direct-acting antiviral (DAA) therapy for chronic hepatitis C virus (HCV) infection. Objective To evaluate whether alcohol use at DAA treatment initiation is associated with decreased likelihood of sustained virologic response (SVR). Design, Setting, and Participants This retrospective cohort study used electronic health records from the US Department of Veterans Affairs (VA), the largest integrated national health care system that provides unrestricted access to HCV treatment. Participants included all patients born between 1945 and 1965 who were dispensed DAA therapy between January 1, 2014, and June 30, 2018. Data analysis was completed in November 2020 with updated sensitivity analyses performed in 2023. Exposure Alcohol use categories were generated using responses to the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire and International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses for alcohol use disorder (AUD): abstinent without history of AUD, abstinent with history of AUD, lower-risk consumption, moderate-risk consumption, and high-risk consumption or AUD. Main Outcomes and Measures The primary outcome was SVR, which was defined as undetectable HCV RNA for 12 weeks or longer after completion of DAA therapy. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% CIs of SVR associated with alcohol category. Results Among 69 229 patients who initiated DAA therapy (mean [SD] age, 62.6 [4.5] years; 67 150 men [97.0%]; 34 655 non-Hispanic White individuals [50.1%]; 28 094 non-Hispanic Black individuals [40.6%]; 58 477 individuals [84.5%] with HCV genotype 1), 65 355 (94.4%) achieved SVR. A total of 32 290 individuals (46.6%) were abstinent without AUD, 9192 (13.3%) were abstinent with AUD, 13 415 (19.4%) had lower-risk consumption, 3117 (4.5%) had moderate-risk consumption, and 11 215 (16.2%) had high-risk consumption or AUD. After adjustment for potential confounding variables, there was no difference in SVR across alcohol use categories, even for patients with high-risk consumption or AUD (OR, 0.95; 95% CI, 0.85-1.07). There was no evidence of interaction by stage of hepatic fibrosis measured by fibrosis-4 score (P for interaction = .30). Conclusions and Relevance In this cohort study, alcohol use and AUD were not associated with lower odds of SVR. Restricting access to DAA therapy according to alcohol use creates an unnecessary barrier to patients and challenges HCV elimination goals.
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Affiliation(s)
- Emily J. Cartwright
- Division of Infectious Diseases, Emory University School of Medicine, Atlanta, Georgia
- Atlanta Veterans Affairs Medical Center, Decatur, Georgia
| | - Chloe Pierret
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Caroline Minassian
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Denise A. Esserman
- Veterans Affairs Connecticut Healthcare System, US Department of Veterans Affairs, West Haven
| | - Janet P. Tate
- Veterans Affairs Connecticut Healthcare System, US Department of Veterans Affairs, West Haven
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Matthew B. Goetz
- Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles
- Veterans Affairs Greater Los Angeles Health Care System, US Department of Veterans Affairs, Los Angeles, California
| | - Debika Bhattacharya
- Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles
- Veterans Affairs Greater Los Angeles Health Care System, US Department of Veterans Affairs, Los Angeles, California
| | - David A. Fiellin
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale School of Public Health, New Haven, Connecticut
| | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System, US Department of Veterans Affairs, West Haven
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale School of Public Health, New Haven, Connecticut
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Christopher T. Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Veterans Affairs Connecticut Healthcare System, US Department of Veterans Affairs, West Haven
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
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Ochoa-Allemant P, Tate JP, Williams EC, Gordon KS, Marconi VC, Bensley KM, Rentsch CT, Wang KH, Taddei TH, Justice AC. Enhanced Identification of Hispanic Ethnicity Using Clinical Data: A Study in the Largest Integrated United States Health Care System. Med Care 2023; 61:200-205. [PMID: 36893404 PMCID: PMC10114212 DOI: 10.1097/mlr.0000000000001824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
BACKGROUND Collection of accurate Hispanic ethnicity data is critical to evaluate disparities in health and health care. However, this information is often inconsistently recorded in electronic health record (EHR) data. OBJECTIVE To enhance capture of Hispanic ethnicity in the Veterans Affairs EHR and compare relative disparities in health and health care. METHODS We first developed an algorithm based on surname and country of birth. We then determined sensitivity and specificity using self-reported ethnicity from the 2012 Veterans Aging Cohort Study survey as the reference standard and compared this to the research triangle institute race variable from the Medicare administrative data. Finally, we compared demographic characteristics and age-adjusted and sex-adjusted prevalence of conditions in Hispanic patients among different identification methods in the Veterans Affairs EHR 2018-2019. RESULTS Our algorithm yielded higher sensitivity than either EHR-recorded ethnicity or the research triangle institute race variable. In 2018-2019, Hispanic patients identified by the algorithm were more likely to be older, had a race other than White, and foreign born. The prevalence of conditions was similar between EHR and algorithm ethnicity. Hispanic patients had higher prevalence of diabetes, gastric cancer, chronic liver disease, hepatocellular carcinoma, and human immunodeficiency virus than non-Hispanic White patients. Our approach evidenced significant differences in burden of disease among Hispanic subgroups by nativity status and country of birth. CONCLUSIONS We developed and validated an algorithm to supplement Hispanic ethnicity information using clinical data in the largest integrated US health care system. Our approach enabled clearer understanding of demographic characteristics and burden of disease in the Hispanic Veteran population.
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Affiliation(s)
| | - Janet P. Tate
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, US Department of Veteran Affairs, West Haven, CT, USA
| | - Emily C. Williams
- Denver-Seattle Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Services Research & Development, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Kirsha S. Gordon
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, US Department of Veteran Affairs, West Haven, CT, USA
| | - Vincent C. Marconi
- Emory University, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Atlanta, GA, USA
| | | | - Christopher T. Rentsch
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, US Department of Veteran Affairs, West Haven, CT, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Karen H. Wang
- Equity Research and Innovation Center, Section of General Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Medical Informatics, Yale School of Medicine, New Haven, CT, USA
| | - Tamar H. Taddei
- VA Connecticut Healthcare System, US Department of Veteran Affairs, West Haven, CT, USA
- Section of Digestive Diseases, Yale School of Medicine, New Haven, CT, USA
| | - Amy C. Justice
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, US Department of Veteran Affairs, West Haven, CT, USA
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA
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6
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Haque LY, Fiellin DA, Tate JP, Esserman D, Bhattacharya D, Butt AA, Crystal S, Edelman EJ, Gordon AJ, Lim JK, Tetrault JM, Williams EC, Bryant K, Cartwright EJ, Rentsch CT, Justice AC, Lo Re V, McGinnis KA. Association Between Alcohol Use Disorder and Receipt of Direct-Acting Antiviral Hepatitis C Virus Treatment. JAMA Netw Open 2022; 5:e2246604. [PMID: 36515952 PMCID: PMC9856353 DOI: 10.1001/jamanetworkopen.2022.46604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
IMPORTANCE Direct-acting antiviral (DAA) treatment for hepatitis C virus (HCV) infection is associated with lower mortality and is effective in individuals with alcohol use disorder (AUD). However, despite recommendations, patients with AUD may be less likely to receive DAAs. OBJECTIVE To assess the association between alcohol use and receipt of DAA treatment among patients with HCV within the Veterans Health Administration (VHA). DESIGN, SETTING, AND PARTICIPANTS This cohort study included 133 753 patients with HCV born from 1945 to 1965 who had completed the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire and had at least 1 outpatient visit in the VHA from January 1, 2014, through May 31, 2017, with maximal follow-up of 3 years until May 31, 2020; DAA receipt; or death, whichever occurred first. EXPOSURES Alcohol use categories generated using responses to the AUDIT-C questionnaire and International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses: current AUD, abstinent with AUD history, at-risk drinking, lower-risk drinking, and abstinent without AUD history. Demographic, other clinical, and pharmacy data were also collected. MAIN OUTCOMES AND MEASURES Associations between alcohol use categories and DAA receipt within 1 and 3 years estimated using Cox proportional hazards regression stratified by calendar year. RESULTS Of 133 753 patients (130 103 men [97%]; mean [SD] age, 60.6 [4.5] years; and 73 493 White patients [55%]), 38% had current AUD, 12% were abstinent with a history of AUD, 6% reported at-risk drinking, 14% reported lower-risk drinking, and 30% were abstinent without a history of AUD. Receipt of DAA treatment within 1 year was 7%, 33%, 53%, and 56% for patients entering the cohort in 2014, 2015, 2016, and 2017, respectively. For patients entering in 2014, those with current AUD (hazard ratio [HR], 0.72 [95%, CI, 0.66-0.77]) or who were abstinent with an AUD history (HR, 0.91 [95% CI, 0.84-1.00]) were less likely to receive DAA treatment within 1 year compared with patients with lower-risk drinking. For those entering in 2015-2017, patients with current AUD (HR, 0.75 [95% CI, 0.70-0.81]) and those who were abstinent with an AUD history (HR, 0.76 [95% CI, 0.68-0.86]) were less likely to receive DAA treatment within 1 year compared with patients with lower-risk drinking. CONCLUSIONS AND RELEVANCE This cohort study suggests that individuals with AUD, regardless of abstinence, were less likely to receive DAA treatment. Improved access to DAA treatment for persons with AUD is needed.
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Affiliation(s)
- Lamia Y. Haque
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
| | - David A. Fiellin
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
| | - Janet P. Tate
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Veterans Affairs Connecticut Health Care System, West Haven
| | - Denise Esserman
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - Debika Bhattacharya
- Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles
- Veterans Affairs Greater Los Angeles Health Care System, Los Angeles, California
| | - Adeel A. Butt
- Department of Medicine, Weill Cornell Medicine, New York, New York
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
- Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | - Stephen Crystal
- Center for Health Services Research, Rutgers University, New Brunswick, New Jersey
| | - E. Jennifer Edelman
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, Connecticut
| | - Adam J. Gordon
- Informatics, Decision-Enhancement, and Analytic Sciences Center, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy, Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Joseph K. Lim
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Jeanette M. Tetrault
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Yale Program in Addiction Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Emily C. Williams
- Seattle-Denver Center of Innovation for Veteran-Centered and Value-Driven Care, Veterans Affairs Puget Sound Health Care System, Seattle, Washington
- Health Services Research and Development, Veterans Affairs Puget Sound Health Care System, Seattle, Washington
- Department of Health Systems and Population Health, University of Washington, Seattle
| | - Kendall Bryant
- HIV/AIDS and Alcohol Research Program, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland
| | - Emily J. Cartwright
- Department of Medicine, Emory School of Medicine, Atlanta, Georgia
- Veterans Affairs Atlanta Health Care System, Atlanta, Georgia
| | - Christopher T. Rentsch
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Veterans Affairs Connecticut Health Care System, West Haven
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Amy C. Justice
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut
- Veterans Affairs Connecticut Health Care System, West Haven
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, Philadelphia, Pennsylvania
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, Philadelphia, Pennsylvania
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, Philadelphia, Pennsylvania
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Dai X, Park JH, Yoo S, D'Imperio N, McMahon BH, Rentsch CT, Tate JP, Justice AC. Survival analysis of localized prostate cancer with deep learning. Sci Rep 2022; 12:17821. [PMID: 36280773 PMCID: PMC9592586 DOI: 10.1038/s41598-022-22118-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 10/10/2022] [Indexed: 01/20/2023] Open
Abstract
In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic Health Record data found in the U.S. Department of Veterans Affairs, the largest integrated healthcare system in the United States, we have developed an automated, personalized risk prediction model to support the clinical decision-making process for localized prostate cancer patients. This method combines the representative power of deep learning and the analytical interpretability of parametric regression models and can implement both time-dependent and static input data. To collect a comprehensive evaluation of model performances, we calculate time-dependent C-statistics [Formula: see text] over 2-, 5-, and 10-year time horizons using either a composite outcome or prostate cancer mortality as the target event. The composite outcome combines the Prostate-Specific Antigen (PSA) test, metastasis, and prostate cancer mortality. Our longitudinal model Recurrent Deep Survival Machine (RDSM) achieved [Formula: see text] 0.85 (0.83), 0.80 (0.83), and 0.76 (0.81), while the cross-sectional model Deep Survival Machine (DSM) attained [Formula: see text] 0.85 (0.82), 0.80 (0.82), and 0.76 (0.79) for the 2-, 5-, and 10-year composite (mortality) outcomes, respectively. In addition to estimating the survival probability, our method can quantify the uncertainty associated with the prediction. The uncertainty scores show a consistent correlation with the prediction accuracy. We find PSA and prostate cancer stage information are the most important indicators in risk prediction. Our work demonstrates the utility of the data-driven machine learning model in prostate cancer risk prediction, which can play a critical role in the clinical decision system.
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Affiliation(s)
- Xin Dai
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA.
| | - Ji Hwan Park
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA
- School of Computer Science, The University of Oklahoma, Norman, OK, USA
| | - Shinjae Yoo
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA
| | - Nicholas D'Imperio
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA
| | - Benjamin H McMahon
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Christopher T Rentsch
- VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Janet P Tate
- VA Connecticut Healthcare System, West Haven, CT, USA
- Schools of Medicine and Public Health, Yale University, New Haven, CT, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, West Haven, CT, USA
- Schools of Medicine and Public Health, Yale University, New Haven, CT, USA
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Danciu I, Agasthya G, Tate JP, Chandra-Shekar M, Goethert I, Ovchinnikova OS, McMahon BH, Justice AC. In with the old, in with the new: machine learning for time to event biomedical research. J Am Med Inform Assoc 2022; 29:1737-1743. [PMID: 35920306 PMCID: PMC9471708 DOI: 10.1093/jamia/ocac106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 05/01/2022] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
The predictive modeling literature for biomedical applications is dominated by biostatistical methods for survival analysis, and more recently some out of the box machine learning approaches. In this article, we show a presentation of a machine learning method appropriate for time-to-event modeling in the area of prostate cancer long-term disease progression. Using XGBoost adapted to long-term disease progression, we developed a predictive model for 118 788 patients with localized prostate cancer at diagnosis from the Department of Veterans Affairs (VA). Our model accounted for patient censoring. Harrell's c-index for our model using only features available at the time of diagnosis was 0.757 95% confidence interval [0.756, 0.757]. Our results show that machine learning methods like XGBoost can be adapted to use accelerated failure time (AFT) with censoring to model long-term risk of disease progression. The long median survival justifies and requires censoring. Overall, we show that an existing machine learning approach can be used for AFT outcome modeling in prostate cancer, and more generally for other chronic diseases with long observation times.
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Affiliation(s)
- Ioana Danciu
- Corresponding Author: Ioana Danciu, Advanced Computing for Health Sciences Group, Oak Ridge National Laboratory, 1 Bethel Valley Road, Building 5700, Oak Ridge, TN 37830, USA;
| | - Greeshma Agasthya
- Advanced Computing for Health Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Janet P Tate
- Department of Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Yale School of Medicine, New Haven, Connecticut, USA
| | - Mayanka Chandra-Shekar
- Advanced Computing for Health Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Ian Goethert
- Advanced Computing for Health Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Olga S Ovchinnikova
- Advanced Computing for Health Sciences Group, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Benjamin H McMahon
- Theoretical Biology Group, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
| | - Amy C Justice
- Department of Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Yale School of Medicine, New Haven, Connecticut, USA
- Yale School of Public Health, New Haven, Connecticut, USA
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McGinnis KA, Justice AC, Moore RD, Silverberg MJ, Althoff KN, Karris M, Lima VD, Crane HM, Horberg MA, Klein MB, Gange SJ, Gebo KA, Mayor A, Tate JP. Discrimination and Calibration of the Veterans Aging Cohort Study Index 2.0 for Predicting Mortality Among People With Human Immunodeficiency Virus in North America. Clin Infect Dis 2022; 75:297-304. [PMID: 34609485 PMCID: PMC9410720 DOI: 10.1093/cid/ciab883] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND The updated Veterans Aging Cohort Study (VACS) Index 2.0 combines general and human immunodeficiency virus (HIV)-specific biomarkers to generate a continuous score that accurately discriminates risk of mortality in diverse cohorts of persons with HIV (PWH), but a score alone is difficult to interpret. Using data from the North American AIDS Cohort Collaboration (NA-ACCORD), we translate VACS Index 2.0 scores into validated probability estimates of mortality. METHODS Because complete mortality ascertainment is essential for accurate calibration, we restricted analyses to cohorts with mortality from the National Death Index or equivalent sources. VACS Index 2.0 components were ascertained from October 1999 to April 2018. Mortality was observed up to March 2019. Calibration curves compared predicted (estimated by fitting a gamma model to the score) to observed mortality overall and within subgroups: cohort (VACS/NA-ACCORD subset), sex, age <50 or ≥50 years, race/ethnicity, HIV-1 RNA ≤500 or >500 copies/mL, CD4 count <350 or ≥350 cells/µL, and years 1999-2009 or 2010-2018. Because mortality rates have decreased over time, the final model was limited to 2010-2018. RESULTS Among 37230 PWH in VACS and 8061 PWH in the NA-ACCORD subset, median age was 53 and 44 years; 3% and 19% were women; and 48% and 39% were black. Discrimination in NA-ACCORD (C-statistic = 0.842 [95% confidence interval {CI}, .830-.854]) was better than in VACS (C-statistic = 0.813 [95% CI, .809-.817]). Predicted and observed mortality largely overlapped in VACS and the NA-ACCORD subset, overall and within subgroups. CONCLUSIONS Based on this validation, VACS Index 2.0 can reliably estimate probability of all-cause mortality, at various follow-up times, among PWH in North America.
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Affiliation(s)
- Kathleen A McGinnis
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Yale Schools of Medicine and Public Health, New Haven, Connecticut, USA
| | | | | | | | - Maile Karris
- University of California, San Diego, San Diego, California, USA
| | | | | | - Michael A Horberg
- Kaiser Permanente Mid-Atlantic Permanente Research Institute, Rockville, Maryland, USA
| | | | | | - Kelly A Gebo
- Johns Hopkins University, Baltimore, Maryland, USA
| | - Angel Mayor
- Universidad Central del Caribe, Bayamon, Puerto Rico, USA
| | - Janet P Tate
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
- Yale School of Medicine, New Haven, Connecticut, USA
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McGinnis KA, Tate JP, Bryant KJ, Justice AC, O'Connor PG, Rodriguez-Barradas MC, Crystal S, Cutter CJ, Hansen NB, Maisto SA, Marconi VC, Williams EC, Cook RL, Gordon AJ, Gordon KS, Eyawo O, Edelman EJ, Fiellin DA. Change in Alcohol Use Based on Self-Report and a Quantitative Biomarker, Phosphatidylethanol, in People With HIV. AIDS Behav 2022; 26:786-794. [PMID: 34542779 DOI: 10.1007/s10461-021-03438-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2021] [Indexed: 10/20/2022]
Abstract
The timeline followback (TLFB) takes more resources to collect than the Alcohol Use Disorder Identification Test (AUDIT-C). We assessed agreement of TLFB and AUDIT-C with the biomarker phosphatidylethanol (PEth) and compared changes in TLFB and PEth among persons with HIV (PWH) using secondary data from randomized trials. We calculated operating characteristics and agreement between TLFB (> 1 and > 2 average drinks/day), AUDIT-C ≥ 4 and PEth ≥ 20 among 275 men with HIV. Median age was 57 years, 80% were African-American; and 17% white. Sixty-eight percent had PEth ≥ 20, 46% reported > 2 average drinks/day on TLFB, 61% reported > 1 average drinks/day on TLFB, and 72% had an AUDIT-C ≥ 4. Relative to PEth, sensitivity for AUDIT-C ≥ 4 was 84% (kappa = 0.36), and for TLFB > 1 average drink/day was 76% (kappa = 0.44). Change in alcohol use appeared greater using TLFB measures than PEth. Strategies to robustly assess alcohol use in PWH may require both self-report and biomarkers.
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Affiliation(s)
- Kathleen A McGinnis
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA.
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | - Kendall J Bryant
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | | | - Maria C Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey VAMC and Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Stephen Crystal
- Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA
| | | | - Nathan B Hansen
- College of Public Health, University of Georgia, Athens, GA, USA
| | - Stephen A Maisto
- Department of Psychology, Syracuse University, Syracuse, NY, USA
| | - Vincent C Marconi
- School of Medicine and Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Atlanta Veterans Affairs Medical Center, Decatur, GA, USA
| | - Emily C Williams
- Department of Health Systems and Population Health, University of Washington School of Public Health and Seattle-Denver Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven Care, VA Puget Sound Healthcare System, Seattle, WA, USA
| | - Robert L Cook
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Adam J Gordon
- University of Utah and Salt Lake City VA Health Care System, Salt Lake City, UT, USA
| | - Kirsha S Gordon
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | | | - E Jennifer Edelman
- Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research On AIDS, Yale School of Public Health, New Haven, CT, USA
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11
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King JT, Yoon JS, Bredl ZM, Habboushe JP, Walker GA, Rentsch CT, Tate JP, Kashyap NM, Hintz RC, Chopra AP, Justice AC. Accuracy of the Veterans Health Administration COVID-19 (VACO) Index for predicting short-term mortality among 1307 US academic medical centre inpatients and 427 224 US Medicare patients. J Epidemiol Community Health 2022; 76:254-260. [PMID: 34583962 PMCID: PMC8483922 DOI: 10.1136/jech-2021-216697] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 09/06/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND The Veterans Health Administration COVID-19 (VACO) Index predicts 30-day all-cause mortality in patients with COVID-19 using age, sex and pre-existing comorbidity diagnoses. The VACO Index was initially developed and validated in a nationwide cohort of US veterans-we now assess its accuracy in an academic medical centre and a nationwide US Medicare cohort. METHODS With measures and weights previously derived and validated in US national Veterans Health Administration (VA) inpatients and outpatients (n=13 323), we evaluated the accuracy of the VACO Index for estimating 30-day all-cause mortality using area under the receiver operating characteristic curve (AUC) and calibration plots of predicted versus observed mortality in inpatients at a single US academic medical centre (n=1307) and in Medicare inpatients and outpatients aged 65+ (n=427 224). RESULTS 30-day mortality varied by data source: VA 8.5%, academic medical centre 17.5%, Medicare 16.0%. The VACO Index demonstrated similar discrimination in VA (AUC=0.82) and academic medical centre inpatient population (AUC=0.80), and when restricted to patients aged 65+ in VA (AUC=0.69) and Medicare inpatient and outpatient data (AUC=0.67). The Index modestly overestimated risk in VA and Medicare data and underestimated risk in Yale New Haven Hospital data. CONCLUSIONS The VACO Index estimates risk of short-term mortality across a wide variety of patients with COVID-19 using data available prior to or at the time of diagnosis. The VACO Index could help inform primary and booster vaccination prioritisation, and indicate who among outpatients testing positive for SARS-CoV-2 should receive greater clinical attention or scarce treatments.
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Affiliation(s)
- Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, USA
| | - James S Yoon
- Yale School of Medicine, New Haven, Connecticut, USA
| | | | - Joseph P Habboushe
- Emergency Medicine, Weill Cornell Medicine, New York, New York, USA
- MDCalc.com, New York, New York, USA
| | - Graham A Walker
- MDCalc.com, New York, New York, USA
- Emergency Medicine, Kaiser Permanente, Oakland, California, USA
| | - Christopher T Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
- Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Nitu M Kashyap
- Yale New Haven Health System, New Haven, Connecticut, USA
| | - Richard C Hintz
- Joint Data Analytics Team, Yale Center for Clinical Investigation, New Haven, Connecticut, USA
| | | | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
- Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
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12
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Torgersen J, Newcomb CW, Carbonari DM, Rentsch CT, Park LS, Mezochow A, Mehta RL, Buchwalder L, Tate JP, Bräu N, Bhattacharya D, Lim JK, Taddei TH, Justice AC, Re VL. Protease inhibitor-based direct-acting antivirals are associated with increased risk of aminotransferase elevations but not hepatic dysfunction or decompensation. J Hepatol 2021; 75:1312-1322. [PMID: 34333102 PMCID: PMC8604762 DOI: 10.1016/j.jhep.2021.07.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 07/14/2021] [Accepted: 07/18/2021] [Indexed: 12/04/2022]
Abstract
BACKGROUND & AIMS Cases of acute liver injury (ALI) have been reported among chronic HCV-infected patients receiving protease inhibitor (PI)-based direct-acting antiviral (DAA) regimens, but no analyses have compared the risk of ALI in patients receiving PI- vs. non-PI-based DAAs. Thus, we compared the risk of 3 ALI outcomes between patients (by baseline Fibrosis-4 [FIB-4] group) receiving PI-based or non-PI-based DAAs. METHODS We conducted a cohort study of 18,498 patients receiving PI-based DAA therapy (paritaprevir/ritonavir/ombitasvir±dasabuvir, elbasvir/grazoprevir, glecaprevir/pibrentasvir) matched 1:1 on propensity score to those receiving non-PI-based DAAs (sofosbuvir/ledipasvir, sofosbuvir/velpatasvir) in the 1945-1965 Veterans Birth Cohort (2014-2019). During exposure to DAA therapy, we determined development of: i) alanine aminotransferase (ALT) >200 U/L, ii) severe hepatic dysfunction (coagulopathy with hyperbilirubinemia), and iii) hepatic decompensation. We used Cox regression to determine hazard ratios (HRs) with 95% CIs for each ALI outcome within groups defined by baseline FIB-4 (≤3.25; >3.25). RESULTS Among patients with baseline FIB-4 ≤3.25, those receiving PIs had a higher risk of ALT >200 U/L (HR 3.98; 95% CI 2.37-6.68), but not severe hepatic dysfunction (HR 0.67; 95% CI 0.19-2.39) or hepatic decompensation (HR 1.01; 95% CI 0.29-3.49), compared to those receiving non-PI-based regimens. For those with baseline FIB-4 >3.25, those receiving PIs had a higher risk of ALT >200 U/L (HR, 2.15; 95% CI 1.09-4.26), but not severe hepatic dysfunction (HR, 1.23 [0.64-2.38]) or hepatic decompensation (HR, 0.87; 95% CI 0.41-1.87), compared to those receiving non-PI-based regimens CONCLUSION: While risk of incident ALT elevations was increased in those receiving PI-based DAAs in both FIB-4 groups, the risk of severe hepatic dysfunction and hepatic decompensation did not differ between patients receiving PI- or non-PI-based DAAs in either FIB-4 group. LAY SUMMARY Cases of liver injury have been reported among patients treated with protease inhibitor-based direct-acting antivirals for hepatitis C infection, but it is not clear if the risk of liver injury among people starting these drugs is increased compared to those starting non-protease inhibitor-based therapy. In this study, patients receiving protease inhibitor-based treatment had a higher risk of liver inflammation than those receiving a non-protease inhibitor-based treatment, regardless of the presence of pre-treatment advanced liver fibrosis/cirrhosis. However, the risk of severe liver dysfunction and decompensation were not higher for patients treated with protease inhibitor-based regimens.
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Affiliation(s)
- Jessie Torgersen
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Craig W. Newcomb
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dena M. Carbonari
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher T. Rentsch
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK,VA Connecticut Healthcare System, West Haven, CT, USA
| | - Lesley S. Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Alyssa Mezochow
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rajni L. Mehta
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Lynn Buchwalder
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Janet P. Tate
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Norbert Bräu
- James J. Peters VA Medical Center, Bronx, NY and Icahn School of Medicine at Mount Sinai, New York, NY
| | - Debika Bhattacharya
- VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Joseph K. Lim
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Tamar H. Taddei
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, CT, USA,Department of Medicine, Yale School of Medicine, New Haven, CT, USA,Division of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA,Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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13
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Akgün KM, Krishnan S, Butt AA, Gibert CL, Graber CJ, Huang L, Pisani MA, Rodriguez-Barradas MC, Hoo GWS, Justice AC, Crothers K, Tate JP. CD4+ cell count and outcomes among HIV-infected compared with uninfected medical ICU survivors in a national cohort. AIDS 2021; 35:2355-2365. [PMID: 34261095 PMCID: PMC8563390 DOI: 10.1097/qad.0000000000003019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND People with HIV (PWH) with access to antiretroviral therapy (ART) experience excess morbidity and mortality compared with uninfected patients, particularly those with persistent viremia and without CD4+ cell recovery. We compared outcomes for medical intensive care unit (MICU) survivors with unsuppressed (>500 copies/ml) and suppressed (≤500 copies/ml) HIV-1 RNA and HIV-uninfected survivors, adjusting for CD4+ cell count. SETTING We studied 4537 PWH [unsuppressed = 38%; suppressed = 62%; 72% Veterans Affairs-based (VA) and 10 531 (64% VA) uninfected Veterans who survived MICU admission after entering the Veterans Aging Cohort Study (VACS) between fiscal years 2001 and 2015. METHODS Primary outcomes were all-cause 30-day and 6-month readmission and mortality, adjusted for demographics, CD4+ cell category (≥350 (reference); 200-349; 50-199; <50), comorbidity and prior healthcare utilization using proportional hazards models. We also adjusted for severity of illness using discharge VACS Index (VI) 2.0 among VA-based survivors. RESULTS In adjusted models, CD4+ categories <350 cells/μl were associated with increased risk for both outcomes up to 6 months, and risk increased with lower CD4+ categories (e.g. 6-month mortality CD4+ 200-349 hazard ratio [HR] = 1.35 [1.12-1.63]; CD4+ <50 HR = 2.14 [1.72-2.66]); unsuppressed status was not associated with outcomes. After adjusting for VI in models stratified by HIV, VI quintiles were strongly associated with both outcomes at both time points. CONCLUSION PWH who survive MICU admissions are at increased risk for worse outcomes compared with uninfected, especially those without CD4+ cell recovery. Severity of illness at discharge is the strongest predictor for outcomes regardless of HIV status. Strategies including intensive case management for HIV-specific and general organ dysfunction may improve outcomes for MICU survivors.
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Affiliation(s)
- Kathleen M Akgün
- Department of Medicine, VA Connecticut Healthcare System, West Haven
- Department of Internal Medicine, Yale University School of Medicine, New Haven
| | - Supriya Krishnan
- Department of Medicine, VA Connecticut Healthcare System, West Haven
- VA Connecticut Healthcare System, West Haven, Connecticut
| | - Adeel A Butt
- Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
- Weill Cornell Medical College, Doha, Quatar and New York, New York, USA
- Hamad Medical Corporation, Doha, Qatar
| | | | - Christopher J Graber
- Infectious Diseases Section, and VA Greater Los Angeles Healthcare System and the Geffen School of Medicine at University of California, Los Angeles
| | - Laurence Huang
- Department of Medicine, Zuckerberg San Francisco, General Hospital and University of California, San Francisco, California
| | - Margaret A Pisani
- Department of Internal Medicine, Yale University School of Medicine, New Haven
| | - Maria C Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey VAMC and Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Guy W Soo Hoo
- Pulmonary and Critical Care Section, VA Greater Los Angeles Healthcare System and Geffen School of Medicine at University of California, Los Angeles, California
| | - Amy C Justice
- Department of Medicine, VA Connecticut Healthcare System, West Haven
- Department of Internal Medicine, Yale University School of Medicine, New Haven
- Yale School of Public Health, New Haven, Connecticut
| | - Kristina Crothers
- Department of Medicine, VA Puget Sound Healthcare System and University of Washington, Seattle, Washington, USA
| | - Janet P Tate
- Department of Internal Medicine, Yale University School of Medicine, New Haven
- VA Connecticut Healthcare System, West Haven, Connecticut
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14
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Gerlovin H, Posner DC, Ho YL, Rentsch CT, Tate JP, King JT, Kurgansky KE, Danciu I, Costa L, Linares FA, Goethert ID, Jacobson DA, Freiberg MS, Begoli E, Muralidhar S, Ramoni RB, Tourassi G, Gaziano JM, Justice AC, Gagnon DR, Cho K. Pharmacoepidemiology, Machine Learning, and COVID-19: An Intent-to-Treat Analysis of Hydroxychloroquine, With or Without Azithromycin, and COVID-19 Outcomes Among Hospitalized US Veterans. Am J Epidemiol 2021; 190:2405-2419. [PMID: 34165150 PMCID: PMC8384407 DOI: 10.1093/aje/kwab183] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 06/03/2021] [Accepted: 06/17/2021] [Indexed: 12/11/2022] Open
Abstract
Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease
2019 (COVID-19) after in vitro studies indicated possible
benefit. Previous in vivo observational studies have presented
conflicting results, though recent randomized clinical trials have reported no
benefit from HCQ amongst hospitalized COVID-19 patients. We examined the effects
of HCQ alone, and in combination with azithromycin, in a hospitalized COVID-19
positive, United States (US) Veteran population using a propensity score
adjusted survival analysis with imputation of missing data. From March 1, 2020
through April 30, 2020, 64,055 US Veterans were tested for COVID-19 based on
Veteran Affairs Healthcare Administration electronic health record data. Of the
7,193 positive cases, 2,809 were hospitalized, and 657 individuals were
prescribed HCQ within the first 48-hours of hospitalization for the treatment of
COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in
combination with azithromycin, and an increased risk of intubation when used in
combination with azithromycin [Hazard Ratio (95% Confidence Interval):
1.55 (1.07, 2.24)]. In conclusion, we assessed the effectiveness of HCQ with or
without azithromycin in treating patients hospitalized with COVID-19 using a
national sample of the US Veteran population. Using rigorous study design and
analytic methods to reduce confounding and bias, we found no evidence of a
survival benefit from the administration of HCQ.
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15
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McGinnis KA, Skanderson M, Justice AC, Akgün KM, Tate JP, King JT, Rentsch CT, Marconi VC, Hsieh E, Ruser C, Kidwai-Khan F, Yousefzadeh R, Erdos J, Park LS. HIV care using differentiated service delivery during the COVID-19 pandemic: a nationwide cohort study in the US Department of Veterans Affairs. J Int AIDS Soc 2021; 24 Suppl 6:e25810. [PMID: 34713585 PMCID: PMC8554215 DOI: 10.1002/jia2.25810] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 08/19/2021] [Indexed: 11/25/2022] Open
Abstract
Introduction The Department of Veterans Affairs (VA) is the largest provider of HIV care in the United States. Changes in healthcare delivery became necessary with the COVID‐19 pandemic. We compared HIV healthcare delivery during the first year of the COVID‐19 pandemic to a prior similar calendar period. Methods We included 27,674 people with HIV (PWH) enrolled in the Veterans Aging Cohort Study prior to 1 March 2019, with ≥1 healthcare encounter from 1 March 2019 to 29 February 2020 (2019) and/or 1 March 2020 to 28 February 2021 (2020). We counted monthly general medicine/infectious disease (GM/ID) clinic visits and HIV‐1 RNA viral load (VL) tests. We determined the percentage with ≥1 clinic visit (in‐person vs. telephone/video [virtual]) and ≥1 VL test (detectable vs. suppressed) for 2019 and 2020. Using pharmacy records, we summarized antiretroviral (ARV) medication refill length (<90 vs. ≥90 days) and monthly ARV coverage. Results Most patients had ≥1 GM/ID visit in 2019 (96%) and 2020 (95%). For 2019, 27% of visits were virtual compared to 64% in 2020. In 2019, 82% had VL measured compared to 74% in 2020. Of those with VL measured, 92% and 91% had suppressed VL in 2019 and 2020. ARV refills for ≥90 days increased from 39% in 2019 to 51% in 2020. ARV coverage was similar for all months of 2019 and 2020 ranging from 76% to 80% except for March 2019 (72%). Women were less likely than men to be on ARVs or to have a VL test in both years. Conclusions During the COVID‐19 pandemic, the VA increased the use of virtual visits and longer ARV refills, while maintaining a high percentage of patients with suppressed VL among those with VL measured. Despite decreased in‐person services during the pandemic, access to ARVs was not disrupted. More follow‐up time is needed to determine whether overall health was impacted by the use of differentiated service delivery and to evaluate whether a long‐term shift to increased virtual healthcare could be beneficial, particularly for PWH in rural areas or with transportation barriers. Programmes to increase ARV use and VL testing for women are needed.
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Affiliation(s)
- Kathleen A McGinnis
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
| | - Melissa Skanderson
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA
| | - Amy C Justice
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Kathleen M Akgün
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Janet P Tate
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Joseph T King
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Christopher T Rentsch
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.,Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Vincent C Marconi
- Emory University School of Medicine, Rollins School of Public Health, and the Atlanta VA Medical Center, Atlanta, Georgia, USA
| | - Evelyn Hsieh
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Christopher Ruser
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Farah Kidwai-Khan
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Roozbeh Yousefzadeh
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Joseph Erdos
- VA CT Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, USA.,Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Lesley S Park
- Stanford Center for Population Health Sciences, Department of Epidemiology and Population Health, Stanford School of Medicine, Stanford, California, USA
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16
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Justice AC, Gordon KS, Romero J, Edelman EJ, Garcia BJ, Jones P, Khoo S, Lo Re V, Rentsch CT, Tate JP, Tseng A, Womack J, Jacobson D. Polypharmacy-associated risk of hospitalisation among people ageing with and without HIV: an observational study. Lancet Healthy Longev 2021; 2:e639-e650. [PMID: 34870254 PMCID: PMC8639138 DOI: 10.1016/s2666-7568(21)00206-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Background Polypharmacy, defined as use of five or more medications concurrently, is associated with adverse health outcomes and people ageing with HIV might be at greater risk than similar uninfected individuals. We aimed to determine whether known pairwise drug interactions (KPDIs) were associated with risk of admission to hospital (hereafter referred to as hospitalisation) and medication count among people ageing with and without HIV after accounting for physiological frailty. Methods In this observational study, we collected individual-level data for participants of the Veterans Aging Cohort Study (VACS) with HIV on antiretroviral therapy (ART) and with supressed HIV-1 RNA and people without HIV who were receiving at least one prescription medication, based on active medications in the 2009 fiscal year (ie, Oct 1, 2008, to Sept 30, 2009). We identified KPDIs among these patients by linking prescription fill and refill data with data from DrugBank (version 5.0.11). We collected data on all-cause mortality and hospitalisations between Oct 1, 2009, and March 31, 2019. We compared KPDI counts using random selection and actual patterns of use across medication counts from two to 12. We created a weighted KPDI Index on the basis of the average association of each KPDI with mortality among people ageing without HIV and used nested Cox models stratified by HIV status to estimate the association between medication count and hospitalisation, with incremental adjustments for demographics, physiological frailty, and KPDI Index. Findings We collected data for 9186 people ageing with HIV and 37 930 individuals without HIV. 45 913 (97·4%) of 47 116 patients were men and the sample was predominantly aged 50–64 years (30 413 [64·6%]). Compared with a random sample of medications, real-world pattern of medication counts and combinations were associated with five-to-six times more KPDIs (eg, for a combination of six medications, KPDI count was 1·09 in the random sample, 5·49 in the HIV-negative population, and 7·13 in the HIV-positive population). For each additional observed medication, people ageing with HIV had approximately 2·94 additional KPDIs and comparators had approximately 2·67 additional KPDIs. Adjustment for demographics, physiological frailty, and KPDI Index reduced the association between medication count and risk of hospitalisation for people ageing with HIV (hazard ratio 1·08 [95% CI 1·07–1·09] reduced to 1·06 [1·05–1·07]) and those without HIV (1·08 [1·07–1·08] reduced to 1·04 [1·03–1·05]). Interpretation For each additional medication, people ageing with HIV have more drug–drug interactions than those without HIV. Adjusting for known non-ART drug–drug interactions, each additional non-ART medication confers excess risk of hospitalisation for people ageing with HIV. Randomised trials will be needed to determine whether reducing these interactions improves outcomes. Funding National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism, Department of Veterans Affairs Health Services Research & Development, and Office of Research and Development.
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Affiliation(s)
- Amy C Justice
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Kirsha S Gordon
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Jonathon Romero
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - E Jennifer Edelman
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Benjamin J Garcia
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Piet Jones
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Saye Khoo
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Vincent Lo Re
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Christopher T Rentsch
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Janet P Tate
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Alice Tseng
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Julie Womack
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
| | - Daniel Jacobson
- School of Medicine, Yale University, New Haven, CT, USA (Prof A C Justice MD, K S Gordon PhD, E J Edelman MD, J P Tate ScD); VA Connecticut Healthcare System, West Haven, CT, USA (Prof A C Justice, K S Gordon, J P Tate, C T Rentsch PhD, J Womack PhD); Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN, USA (J Romero BSc, P Jones MSc); Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA (B J Garcia PhD, D Jacobson PhD); Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK (Prof S Khoo MD); Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA (V Lo Re III MD); Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (C T Rentsch); University Health Network and Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada (A Tseng PharmD); Faculty of Yale University School of Nursing, West Haven, CT, USA (J Womack)
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17
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Weinstein EJ, Stephens-Shields A, Loabile B, Yuh T, Silibovsky R, Nelson CL, O'Donnell JA, Hsieh E, Hanberg JS, Akgün KM, Tate JP, Lo Re V. Development and validation of case-finding algorithms to identify prosthetic joint infections after total knee arthroplasty in Veterans Health Administration data. Pharmacoepidemiol Drug Saf 2021; 30:1184-1191. [PMID: 34170057 DOI: 10.1002/pds.5316] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/17/2021] [Accepted: 06/21/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To determine the positive predictive values (PPVs) of ICD-9, ICD-10, and current procedural terminology (CPT)-based diagnostic coding algorithms to identify prosthetic joint infection (PJI) following knee arthroplasty (TKA) within the United States Veterans Health Administration. METHODS We identified patients with: (1) hospital discharge ICD-9 or ICD-10 diagnosis of PJI, (2) ICD-9, ICD-10, or CPT procedure code for TKA prior to PJI diagnosis, (3) CPT code for knee X-ray within ±90 days of the PJI diagnosis, and (4) at least 1 CPT code for arthrocentesis, arthrotomy, blood culture, or microbiologic procedure within ±90 days of the PJI diagnosis date. Separate samples of patients identified with the ICD-9 and ICD-10-based PJI diagnoses were obtained, stratified by TKA procedure volume at each medical center. Medical records of sampled patients were reviewed by infectious disease clinicians to adjudicate PJI events. The PPV (95% confidence interval [CI]) for the ICD-9 and ICD-10 PJI algorithms were calculated. RESULTS Among a sample of 80 patients meeting the ICD-9 PJI algorithm, 60 (PPV 75.0%, [CI 64.1%-84.0%]) had confirmed PJI. Among 80 patients who met the ICD-10 PJI algorithm, 68 (PPV 85.0%, [CI 75.3%-92.0%]) had a confirmed diagnosis. CONCLUSIONS An algorithm consisting of an ICD-9 or ICD-10 PJI diagnosis following a TKA code combined with CPT codes for a knee X-ray and either a relevant surgical procedure or microbiologic culture yielded a PPV of 75.0% (ICD-9) and 85.0% (ICD-10), for confirmed PJI events and could be considered for use in future pharmacoepidemiologic studies.
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Affiliation(s)
- Erica J Weinstein
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alisa Stephens-Shields
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Bogadi Loabile
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Tiffany Yuh
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Randi Silibovsky
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Charles L Nelson
- Department of Orthopedic Surgery, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Judith A O'Donnell
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Evelyn Hsieh
- VA Connecticut Health System, West Haven, Connecticut, USA.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.,Section of Rheumatology, Allergy and Immunology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Jennifer S Hanberg
- VA Connecticut Health System, West Haven, Connecticut, USA.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.,Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Kathleen M Akgün
- VA Connecticut Health System, West Haven, Connecticut, USA.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Janet P Tate
- VA Connecticut Health System, West Haven, Connecticut, USA.,Department of Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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18
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Torgersen J, Kallan MJ, Carbonari DM, Park LS, Mehta RL, D'Addeo K, Tate JP, Lim JK, Goetz MB, Rodriguez-Barradas MC, Gibert CL, Bräu N, Brown ST, Roy JA, Taddei TH, Justice AC, Lo Re V. HIV RNA, CD4+ Percentage, and Risk of Hepatocellular Carcinoma by Cirrhosis Status. J Natl Cancer Inst 2021; 112:747-755. [PMID: 31687755 DOI: 10.1093/jnci/djz214] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 09/19/2019] [Accepted: 10/25/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Despite increasing incidence of hepatocellular carcinoma (HCC) among HIV-infected patients, it remains unclear if HIV-related factors contribute to development of HCC. We examined if higher or prolonged HIV viremia and lower CD4+ cell percentage were associated with HCC. METHODS We conducted a cohort study of HIV-infected individuals who had HIV RNA, CD4+, and CD8+ cell counts and percentages assessed in the Veterans Aging Cohort Study (1999-2015). HCC was ascertained using Veterans Health Administration cancer registries and electronic records. Cox regression was used to determine hazard ratios (HR, 95% confidence interval [CI]) of HCC associated with higher current HIV RNA, longer duration of detectable HIV viremia (≥500 copies/mL), and current CD4+ cell percentage less than 14%, adjusting for traditional HCC risk factors. Analyses were stratified by previously validated diagnoses of cirrhosis prior to start of follow-up. RESULTS Among 35 659 HIV-infected patients, 302 (0.8%) developed HCC over 281 441 person-years (incidence rate = 107.3 per 100 000 person-years). Among patients without baseline cirrhosis, higher HIV RNA (HR = 1.25, 95% CI = 1.12 to 1.40, per 1.0 log10 copies/mL) and 12 or more months of detectable HIV (HR = 1.47, 95% CI = 1.02 to 2.11) were independently associated with higher risk of HCC. CD4+ percentage less than 14% was not associated with HCC in any model. Hepatitis C coinfection was a statistically significant predictor of HCC regardless of baseline cirrhosis status. CONCLUSION Among HIV-infected patients without baseline cirrhosis, higher HIV RNA and longer duration of HIV viremia increased risk of HCC, independent of traditional HCC risk factors. This is the strongest evidence to date that HIV viremia contributes to risk of HCC in this group.
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Affiliation(s)
- Jessie Torgersen
- Division of Infectious Diseases, Department of Medicine.,Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training
| | - Michael J Kallan
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training
| | - Dena M Carbonari
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training
| | - Lesley S Park
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA
| | - Rajni L Mehta
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Kathryn D'Addeo
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Janet P Tate
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Joseph K Lim
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Matthew Bidwell Goetz
- VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Maria C Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey VA Medical Center and Department of Medicine, Baylor College of Medicine, Houston, TX
| | - Cynthia L Gibert
- Washington DC VA Medical Center and George Washington University Medical Center, Washington, DC
| | - Norbert Bräu
- James J. Peters VA Medical Center, Bronx, NY, and Icahn School of Medicine at Mount Sinai, New York, NY
| | - Sheldon T Brown
- James J. Peters VA Medical Center, Bronx, NY, and Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jason A Roy
- Department of Biostatistics, Rutgers University School of Public Health, New Brunswick, NJ
| | - Tamar H Taddei
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Amy C Justice
- VA Connecticut Healthcare System, West Haven, CT.,Yale University School of Medicine, New Haven, CT
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine.,Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Pharmacoepidemiology Research and Training
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Rentsch CT, Beckman JA, Tomlinson L, Gellad WF, Alcorn C, Kidwai-Khan F, Skanderson M, Brittain E, King JT, Ho YL, Eden S, Kundu S, Lann MF, Greevy RA, Ho PM, Heidenreich PA, Jacobson DA, Douglas IJ, Tate JP, Evans SJW, Atkins D, Justice AC, Freiberg MS. Early initiation of prophylactic anticoagulation for prevention of coronavirus disease 2019 mortality in patients admitted to hospital in the United States: cohort study. BMJ 2021; 372:n311. [PMID: 33574135 PMCID: PMC7876672 DOI: 10.1136/bmj.n311] [Citation(s) in RCA: 137] [Impact Index Per Article: 45.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To evaluate whether early initiation of prophylactic anticoagulation compared with no anticoagulation was associated with decreased risk of death among patients admitted to hospital with coronavirus disease 2019 (covid-19) in the United States. DESIGN Observational cohort study. SETTING Nationwide cohort of patients receiving care in the Department of Veterans Affairs, a large integrated national healthcare system. PARTICIPANTS All 4297 patients admitted to hospital from 1 March to 31 July 2020 with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and without a history of anticoagulation. MAIN OUTCOME MEASURES The main outcome was 30 day mortality. Secondary outcomes were inpatient mortality, initiating therapeutic anticoagulation (a proxy for clinical deterioration, including thromboembolic events), and bleeding that required transfusion. RESULTS Of 4297 patients admitted to hospital with covid-19, 3627 (84.4%) received prophylactic anticoagulation within 24 hours of admission. More than 99% (n=3600) of treated patients received subcutaneous heparin or enoxaparin. 622 deaths occurred within 30 days of hospital admission, 513 among those who received prophylactic anticoagulation. Most deaths (510/622, 82%) occurred during hospital stay. Using inverse probability of treatment weighted analyses, the cumulative incidence of mortality at 30 days was 14.3% (95% confidence interval 13.1% to 15.5%) among those who received prophylactic anticoagulation and 18.7% (15.1% to 22.9%) among those who did not. Compared with patients who did not receive prophylactic anticoagulation, those who did had a 27% decreased risk for 30 day mortality (hazard ratio 0.73, 95% confidence interval 0.66 to 0.81). Similar associations were found for inpatient mortality and initiation of therapeutic anticoagulation. Receipt of prophylactic anticoagulation was not associated with increased risk of bleeding that required transfusion (hazard ratio 0.87, 0.71 to 1.05). Quantitative bias analysis showed that results were robust to unmeasured confounding (e-value lower 95% confidence interval 1.77 for 30 day mortality). Results persisted in several sensitivity analyses. CONCLUSIONS Early initiation of prophylactic anticoagulation compared with no anticoagulation among patients admitted to hospital with covid-19 was associated with a decreased risk of 30 day mortality and no increased risk of serious bleeding events. These findings provide strong real world evidence to support guidelines recommending the use of prophylactic anticoagulation as initial treatment for patients with covid-19 on hospital admission.
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Affiliation(s)
- Christopher T Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
| | - Joshua A Beckman
- Cardiovascular Division, Vanderbilt University Medical Center and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Laurie Tomlinson
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Walid F Gellad
- Center for Pharmaceutical Policy and Prescribing, Health Policy Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Division of General Internal Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Veterans Affairs Pittsburgh Healthcare System, US Department of Veterans Affairs, Pittsburgh, PA, USA
| | - Charles Alcorn
- Center for Occupational Biostatistics and Epidemiology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
| | - Evan Brittain
- Department of Medicine, Vanderbilt University Medical Center and Vanderbilt Translational and Clinical Cardiovascular Research Center, Nashville, TN, USA
| | - Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Svetlana Eden
- Faculty of Biostatistics, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Suman Kundu
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael F Lann
- Center for Occupational Biostatistics and Epidemiology, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert A Greevy
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - P Michael Ho
- Rocky Mountain Regional VA Medical Center, US Department of Veterans Affairs, Aurora, CO, USA
| | - Paul A Heidenreich
- VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Daniel A Jacobson
- Oak Ridge National Laboratory, Biosciences Division, Oak Ridge, TN, USA
| | - Ian J Douglas
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Stephen J W Evans
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK
| | - David Atkins
- Health Services Research and Development, US Department of Veterans Affairs, Washington, DC, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Matthew S Freiberg
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Geriatric Research Education and Clinical Center, Tennessee Valley Healthcare System, US Department of Veterans Affairs, Nashville, TN, USA
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20
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Bedimo RJ, Park LS, Shebl FM, Sigel K, Rentsch CT, Crothers K, Rodriguez-Barradas MC, Goetz MB, Butt AA, Brown ST, Gibert C, Justice AC, Tate JP. Statin exposure and risk of cancer in people with and without HIV infection. AIDS 2021; 35:325-334. [PMID: 33181533 PMCID: PMC7775280 DOI: 10.1097/qad.0000000000002748] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE To determine whether statin exposure is associated with decreased cancer and mortality risk among persons with HIV (PWH) and uninfected persons. Statins appear to have immunomodulatory and anti-inflammatory effects and may reduce cancer risk, particularly among PWH as they experience chronic inflammation and immune activation. DESIGN Propensity score-matched cohort of statin-exposed and unexposed patients from 2002 to 2017 in the Veterans Aging Cohort Study (VACS), a large cohort with cancer registry linkage and detailed pharmacy data. METHODS We calculated Cox regression hazard ratios (HRs) and 95% confidence intervals (CI) associated with statin use for all cancers, microbial cancers (associated with bacterial or oncovirus coinfection), nonmicrobial cancers, and mortality. RESULTS :The propensity score-matched sample (N = 47 940) included 23 970 statin initiators (31% PWH). Incident cancers were diagnosed in 1160 PWH and 2116 uninfected patients. Death was reported in 1667 (7.0%) statin-exposed, and 2215 (9.2%) unexposed patients. Statin use was associated with 24% decreased risk of microbial-associated cancers (hazard ratio 0.76; 95% CI 0.69-0.85), but was not associated with nonmicrobial cancer risk (hazard ratio 1.00; 95% CI 0.92-1.09). Statin use was associated with 33% lower risk of death overall (hazard ratio 0.67; 95% CI 0.63-0.72). Results were similar in analyses stratified by HIV status, except for non-Hodgkin lymphoma where statin use was associated with reduced risk (hazard ratio 0.56; 95% CI 0.38-0.83) for PWH, but not for uninfected (P interaction = 0.012). CONCLUSION In both PWH and uninfected, statin exposure was associated with lower risk of microbial, but not nonmicrobial cancer incidence, and with decreased mortality.
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Affiliation(s)
- Roger J Bedimo
- Veterans Affairs North Texas Healthcare System, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Lesley S Park
- Stanford University School of Medicine, Palo Alto, California
| | - Fatima M Shebl
- Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Keith Sigel
- Icahn School of Medicine at Mt. Sinai, New York, New York, USA
| | | | - Kristina Crothers
- VA Puget Sound Healthcare System, University of Washington School of Medicine, Seattle, Washington
| | | | - Matthew Bidwell Goetz
- Veterans Affairs Greater Los Angeles Healthcare System, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Adeel A Butt
- VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvamia
- Weill Cornell Medical College, New York, New York, USA
- Weill Cornell Medical College, Doha, Qatar
| | - Sheldon T Brown
- James J. Peters Veterans Affairs Medical Center, Bronx
- Icahn School of Medicine at Mt. Sinai, New York, New York
| | - Cynthia Gibert
- Washington DC Veterans Affairs Medical Center, George Washington University School of Medicine and Health Sciences, Washington, DC
| | - Amy C Justice
- VA Connecticut Healthcare System, West Haven
- Yale School of Medicine, New Haven, Connecticut, USA
| | - Janet P Tate
- VA Connecticut Healthcare System, West Haven
- Yale School of Medicine, New Haven, Connecticut, USA
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21
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Eyawo O, Deng Y, Dziura J, Justice AC, McGinnis K, Tate JP, Rodriguez-Barradas MC, Hansen NB, Maisto SA, Marconi VC, O'Connor PG, Bryant K, Fiellin DA, Edelman EJ. Validating Self-Reported Unhealthy Alcohol Use With Phosphatidylethanol (PEth) Among Patients With HIV. Alcohol Clin Exp Res 2021; 44:2053-2063. [PMID: 33460225 DOI: 10.1111/acer.14435] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 08/04/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND We sought to compare self-reported alcohol consumption using Timeline Followback (TLFB) to biomarker-based evidence of significant alcohol use (phosphatidylethanol [PEth] > 20 ng/ml). Using data from patients with HIV (PWH) entering a clinical trial, we asked whether TLFB could predict PEth > 20 ng/ml and assessed the magnitude of association between TLFB and PEth level. METHODS We defined unhealthy alcohol use as any alcohol use in the presence of liver disease, at-risk drinking, or alcohol use disorder. Self-reported alcohol use obtained from TLFB interview was assessed as mean number of drinks/day and number of heavy drinking days over the past 21 days. Dried blood spot samples for PEth were collected at the interview. We used logistic regression to predict PEth > 20 ng/ml and Spearman correlation to quantify the association with PEth, both as a function of TLFB. RESULTS Among 282 individuals (99% men) in the analytic sample, approximately two-thirds (69%) of individuals had PEth > 20 ng/ml. The proportion with PEth > 20 ng/ml increased with increasing levels of self-reported alcohol use; of the 190 patients with either at-risk drinking or alcohol use disorder based on self-report, 82% had PEth > 20 ng/ml. Discrimination was better with number of drinks per day than heavy drinking days (AUC: 0.80 [95% CI: 0.74 to 0.85] vs. 0.74 [95% CI: 0.68 to 0.80]). The number of drinks per day and PEth were significantly and positively correlated across all levels of alcohol use (Spearman's R ranged from 0.29 to 0.56, all p values < 0.01). CONCLUSIONS In this sample of PWH entering a clinical trial, mean numbers of drinks per day discriminated individuals with evidence of significant alcohol use by PEth. PEth complements self-report to improve identification of self-reported unhealthy alcohol use among PWH.
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Affiliation(s)
- Oghenowede Eyawo
- School of Global Health, Faculty of Health, York University, Toronto, ON, Canada.,Veterans Aging Cohort Study Coordinating Center, (OE, ACJ, KM, JPT), West Haven VA Healthcare System, West Haven, Connecticut
| | - Yanhong Deng
- Yale Center for Analytic Sciences, (YD, JD), Yale University School of Public Health, New Haven, Connecticut
| | - James Dziura
- Yale Center for Analytic Sciences, (YD, JD), Yale University School of Public Health, New Haven, Connecticut
| | - Amy C Justice
- Veterans Aging Cohort Study Coordinating Center, (OE, ACJ, KM, JPT), West Haven VA Healthcare System, West Haven, Connecticut.,Yale School of Medicine, (ACJ, JPT, PGO, DAF, EJE), New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, (ACJ, NBH, DAF, EJE), Yale School of Public Health, New Haven, Connecticut
| | - Kathleen McGinnis
- Veterans Aging Cohort Study Coordinating Center, (OE, ACJ, KM, JPT), West Haven VA Healthcare System, West Haven, Connecticut
| | - Janet P Tate
- Veterans Aging Cohort Study Coordinating Center, (OE, ACJ, KM, JPT), West Haven VA Healthcare System, West Haven, Connecticut.,Yale School of Medicine, (ACJ, JPT, PGO, DAF, EJE), New Haven, Connecticut
| | | | - Nathan B Hansen
- Center for Interdisciplinary Research on AIDS, (ACJ, NBH, DAF, EJE), Yale School of Public Health, New Haven, Connecticut.,College of Public Health, (NBH), University of Georgia, Athens, Georgia
| | - Stephen A Maisto
- Department of Psychology, (SAM), Syracuse University, Syracuse, New York
| | - Vincent C Marconi
- Atlanta Veterans Affairs Medical Center, (VCM), Emory University School of Medicine, Atlanta, Georgia
| | - Patrick G O'Connor
- Yale School of Medicine, (ACJ, JPT, PGO, DAF, EJE), New Haven, Connecticut
| | - Kendall Bryant
- National Institute on Alcohol Abuse and Alcoholism HIV/AIDS Program, (KB), Bethesda, Maryland
| | - David A Fiellin
- Yale School of Medicine, (ACJ, JPT, PGO, DAF, EJE), New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, (ACJ, NBH, DAF, EJE), Yale School of Public Health, New Haven, Connecticut
| | - E Jennifer Edelman
- Yale School of Medicine, (ACJ, JPT, PGO, DAF, EJE), New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, (ACJ, NBH, DAF, EJE), Yale School of Public Health, New Haven, Connecticut
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22
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Zifodya JS, Duncan MS, So‐Armah KA, Attia EF, Akgün KM, Rodriguez‐Barradas MC, Marconi VC, Budoff MJ, Bedimo RJ, Alcorn CW, Soo Hoo GW, Butt AA, Kim JW, Sico JJ, Tindle HA, Huang L, Tate JP, Justice AC, Freiberg MS, Crothers K. Community-Acquired Pneumonia and Risk of Cardiovascular Events in People Living With HIV. J Am Heart Assoc 2020; 9:e017645. [PMID: 33222591 PMCID: PMC7763776 DOI: 10.1161/jaha.120.017645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 10/16/2020] [Indexed: 01/26/2023]
Abstract
Background Hospitalization with community-acquired pneumonia (CAP) is associated with an increased risk of cardiovascular disease (CVD) events in patients uninfected with HIV. We evaluated whether people living with HIV (PLWH) have a higher risk of CVD or mortality than individuals uninfected with HIV following hospitalization with CAP. Methods and Results We analyzed data from the Veterans Aging Cohort Study on US veterans admitted with their first episode of CAP from April 2003 through December 2014. We used Cox regression analyses to determine whether HIV status was associated with incident CVD events and mortality from date of admission through 30 days after discharge (30-day mortality), adjusting for known CVD risk factors. We included 4384 patients (67% [n=2951] PLWH). PLWH admitted with CAP were younger, had less severe CAP, and had fewer CVD risk factors than patients with CAP who were uninfected with HIV. In multivariable-adjusted analyses, CVD risk was similar in PLWH compared with HIV-uninfected (hazard ratio [HR], 0.89; 95% CI, 0.70-1.12), but HIV infection was associated with higher mortality risk (HR, 1.49; 95% CI, 1.16-1.90). In models stratified by HIV status, CAP severity was significantly associated with incident CVD and 30-day mortality in PLWH and patients uninfected with HIV. Conclusions In this study, the risk of CVD events during or after hospitalization for CAP was similar in PLWH and patients uninfected with HIV, after adjusting for known CVD risk factors and CAP severity. HIV infection, however, was associated with increased 30-day mortality after CAP hospitalization in multivariable-adjusted models. PLWH should be included in future studies evaluating mechanisms and prevention of CVD events after CAP.
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Affiliation(s)
- Jerry S. Zifodya
- Department of MedicineSection of Pulmonary Diseases, Critical Care, and Environmental MedicineTulane University School of MedicineNew OrleansLA
| | - Meredith S. Duncan
- Department of MedicineDivision of Cardiovascular MedicineVanderbilt University Medical CenterNashvilleTN
- Department of BiostatisticsCollege of Public HealthUniversity of KentuckyLexingtonKY
| | - Kaku A. So‐Armah
- Section of General Internal MedicineBoston University School of MedicineBostonMA
| | - Engi F. Attia
- Department of MedicineDivision of Pulmonary, Critical Care, and Sleep MedicineUniversity of WashingtonSeattleWA
| | - Kathleen M. Akgün
- Department of MedicineSection of Pulmonary, Critical Care and Sleep MedicineVeterans Affairs Connecticut Healthcare SystemWest HavenCT
- Yale University School of MedicineNew HavenCT
| | - Maria C. Rodriguez‐Barradas
- Infectious Diseases SectionMichael E. DeBakey Veterans Affairs Medical CenterBaylor College of MedicineHoustonTX
| | - Vincent C. Marconi
- Atlanta Veterans Affairs Medical CenterDivision of Infectious DiseasesDepartment of Global HealthRollins School of Public Health and Department of MedicineEmory University School of MedicineAtlantaGA
| | - Matthew J. Budoff
- Department of CardiologyLos Angeles Biomedical Research Institute at Harbor‐UCLALos AngelesCA
| | - Roger J. Bedimo
- Department of MedicineVA North Texas Health Care System and University of Texas Southwestern Medical CenterDallasTX
| | - Charles W. Alcorn
- Department of BiostatisticsGraduate School of Public HealthUniversity of PittsburghPA
| | - Guy W. Soo Hoo
- Department of MedicinePulmonary, Critical Care and Sleep SectionVeterans Affairs Greater Los Angeles Healthcare SystemLos AngelesCA
| | - Adeel A. Butt
- Veterans AffairsPittsburgh Healthcare SystemPittsburghPA
- Weill Cornell Medical CollegeNew YorkNY
- Weill Cornell Medical CollegeDohaQatar
| | - Joon W. Kim
- Critical Care MedicineJames J. Peters Veterans Affairs Medical CenterBronxNY
| | - Jason J. Sico
- Neurology Service and Clinical Epidemiology Research Center (CERC)Veterans Affairs Connecticut Healthcare SystemWest HavenCT
- Departments of Internal MedicineSection of Internal Medicine, NeurologySections of Vascular Neurology and General NeurologyCenter for NeuroEpidemiological and Clinical ResearchYale School of MedicineNew HavenCT
| | - Hilary A. Tindle
- Geriatric Research Education and Clinical Centers (GRECC)Veterans Affairs Tennessee Valley Healthcare SystemNashvilleTN
- Department of MedicineDivision of General Internal Medicine and Public HealthVanderbilt University Medical CenterNashvilleTN
| | - Laurence Huang
- Department of MedicineZuckerberg San Francisco General HospitalUniversity of California San FranciscoSan FranciscoCA
| | - Janet P. Tate
- Department of MedicineSection of Pulmonary, Critical Care and Sleep MedicineVeterans Affairs Connecticut Healthcare SystemWest HavenCT
- Yale University School of MedicineNew HavenCT
| | - Amy C. Justice
- Yale University School of MedicineNew HavenCT
- Department of MedicineVeterans Affairs Connecticut Healthcare SystemWest HavenCT
| | - Matthew S. Freiberg
- Department of MedicineDivision of Cardiovascular MedicineVanderbilt University Medical CenterNashvilleTN
- Department of MedicineDivision of General Internal Medicine and Public HealthVanderbilt University Medical CenterNashvilleTN
| | - Kristina Crothers
- Department of MedicineDivision of Pulmonary, Critical Care, and Sleep MedicineUniversity of WashingtonSeattleWA
- Veterans Affairs Puget Sound Health Care SystemSeattleWA
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23
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King JT, Yoon JS, Rentsch CT, Tate JP, Park LS, Kidwai-Khan F, Skanderson M, Hauser RG, Jacobson DA, Erdos J, Cho K, Ramoni R, Gagnon DR, Justice AC. Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index. PLoS One 2020; 15:e0241825. [PMID: 33175863 PMCID: PMC7657526 DOI: 10.1371/journal.pone.0241825] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 10/21/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. METHODS AND FINDINGS We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality-no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77-0.81), and in early (AUC = 0.81 95% CI: 0.78-0.83) and late (AUC = 0.84, 95% CI: 0.78-0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60-64 years, overall mortality was estimated at 9% (95% CI: 6-11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3-7%) to 21% (95% CI: 12-31%), depending on sex and comorbid disease. CONCLUSION Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines.
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Affiliation(s)
- Joseph T. King
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - James S. Yoon
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, United States of America
- Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Christopher T. Rentsch
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Janet P. Tate
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Lesley S. Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, California, United States of America
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Melissa Skanderson
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
| | - Ronald G. Hauser
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Daniel A. Jacobson
- Oak Ridge National Laboratory, Biosciences Division, Oak Ridge, Tennessee, United States of America
- The Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee Knoxville, Knoxville, Tennessee, United States of America
- Department of Psychology, University of Tennessee Knoxville, Knoxville, Tennesee, United States of America
| | - Joseph Erdos
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Kelly Cho
- VA Boston Healthcare System, U.S. Department of Veterans Affairs, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Aging, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - Rachel Ramoni
- Office of Research and Development, Veterans Health Administration, United States Department of Veterans Affairs, Washington, DC, United States of America
| | - David R. Gagnon
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Amy C. Justice
- VA Connecticut Healthcare System, U.S. Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
- Yale School of Public Health, New Haven, Connecticut, United States of America
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24
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Zhou H, Rentsch CT, Cheng Z, Kember RL, Nunez YZ, Sherva RM, Tate JP, Dao C, Xu K, Polimanti R, Farrer LA, Justice AC, Kranzler HR, Gelernter J. Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study. JAMA Psychiatry 2020; 77:1072-1080. [PMID: 32492095 PMCID: PMC7270886 DOI: 10.1001/jamapsychiatry.2020.1206] [Citation(s) in RCA: 92] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
IMPORTANCE With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). OBJECTIVES To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. DESIGN, SETTING, AND PARTICIPANTS A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. MAIN OUTCOMES AND MEASURES Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). RESULTS A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (μ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: β = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. CONCLUSIONS AND RELEVANCE This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.
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Affiliation(s)
- Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Christopher T. Rentsch
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven,Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut,Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Zhongshan Cheng
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Rachel L. Kember
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia,Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Yaira Z. Nunez
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Richard M. Sherva
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts
| | - Janet P. Tate
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven,Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Cecilia Dao
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven,Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, Massachusetts,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts,Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts,Department of Neurology, Boston University School of Medicine, Boston, Massachusetts,Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts
| | - Amy C. Justice
- Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven,Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut,Yale School of Public Health, New Haven, Connecticut
| | - Henry R. Kranzler
- Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut,Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven,Department of Genetics, Yale University School of Medicine, New Haven, Connecticut,Department of Neuroscience, Yale University School of Medicine, New Haven, Connecticut
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Justice AC, Tate JP. Strengths and Limitations of the Veterans Aging Cohort Study Index as a Measure of Physiologic Frailty. AIDS Res Hum Retroviruses 2020; 35:1023-1033. [PMID: 31565954 DOI: 10.1089/aid.2019.0136] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The Veterans Aging Cohort Study Index (VACS Index) is an index comprised of routine clinical laboratory tests that accurately and generalizably predicts all-cause mortality among those living with and without HIV infection. Increasing evidence supports its use as a measure of physiologic frailty among those aging with HIV because of its associations with frailty related outcomes including mortality, hospitalization, fragility fractures, serious falls, pneumonia, cognitive decline, delirium, and functional decline. In this review, we explore the evidence supporting the validity (construct, correlative, and predictive), responsiveness, and feasibility of the VACS Index as an early indicator of physiologic frailty. We also consider its limitations.
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Affiliation(s)
- Amy C. Justice
- VA Connecticut Healthcare System, West Haven, Connecticut
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Janet P. Tate
- VA Connecticut Healthcare System, West Haven, Connecticut
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
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26
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Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King JT, Skanderson M, Hauser RG, Schultze A, Jarvis CI, Holodniy M, Lo Re V, Akgün KM, Crothers K, Taddei TH, Freiberg MS, Justice AC. Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study. PLoS Med 2020; 17:e1003379. [PMID: 32960880 PMCID: PMC7508372 DOI: 10.1371/journal.pmed.1003379] [Citation(s) in RCA: 211] [Impact Index Per Article: 52.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 08/31/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19). We investigated racial and ethnic disparities in patterns of COVID-19 testing (i.e., who received testing and who tested positive) and subsequent mortality in the largest integrated healthcare system in the United States. METHODS AND FINDINGS This retrospective cohort study included 5,834,543 individuals receiving care in the US Department of Veterans Affairs; most (91%) were men, 74% were non-Hispanic White (White), 19% were non-Hispanic Black (Black), and 7% were Hispanic. We evaluated associations between race/ethnicity and receipt of COVID-19 testing, a positive test result, and 30-day mortality, with multivariable adjustment for a wide range of demographic and clinical characteristics including comorbid conditions, health behaviors, medication history, site of care, and urban versus rural residence. Between February 8 and July 22, 2020, 254,595 individuals were tested for COVID-19, of whom 16,317 tested positive and 1,057 died. Black individuals were more likely to be tested (rate per 1,000 individuals: 60.0, 95% CI 59.6-60.5) than Hispanic (52.7, 95% CI 52.1-53.4) and White individuals (38.6, 95% CI 38.4-38.7). While individuals from minority backgrounds were more likely to test positive (Black versus White: odds ratio [OR] 1.93, 95% CI 1.85-2.01, p < 0.001; Hispanic versus White: OR 1.84, 95% CI 1.74-1.94, p < 0.001), 30-day mortality did not differ by race/ethnicity (Black versus White: OR 0.97, 95% CI 0.80-1.17, p = 0.74; Hispanic versus White: OR 0.99, 95% CI 0.73-1.34, p = 0.94). The disparity between Black and White individuals in testing positive for COVID-19 was stronger in the Midwest (OR 2.66, 95% CI 2.41-2.95, p < 0.001) than the West (OR 1.24, 95% CI 1.11-1.39, p < 0.001). The disparity in testing positive for COVID-19 between Hispanic and White individuals was consistent across region, calendar time, and outbreak pattern. Study limitations include underrepresentation of women and a lack of detailed information on social determinants of health. CONCLUSIONS In this nationwide study, we found that Black and Hispanic individuals are experiencing an excess burden of SARS-CoV-2 infection not entirely explained by underlying medical conditions or where they live or receive care. There is an urgent need to proactively tailor strategies to contain and prevent further outbreaks in racial and ethnic minority communities.
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Affiliation(s)
- Christopher T. Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Janet P. Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Lesley S. Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, California, United States of America
| | - Joseph T. King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
| | - Ronald G. Hauser
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Anna Schultze
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Christopher I. Jarvis
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Mark Holodniy
- VA Palo Alto Health Care System, US Department of Veterans Affairs, Palo Alto, California, United States of America
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Kathleen M. Akgün
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Kristina Crothers
- VA Puget Sound Health Care System, US Department of Veterans Affairs, Seattle, Washington, United States of America
- Department of Medicine, University of Washington School of Medicine, Seattle, Washington, United States of America
| | - Tamar H. Taddei
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Matthew S. Freiberg
- Geriatric Research Education and Clinical Center, Tennessee Valley Healthcare System, US Department of Veterans Affairs, Nashville, Tennessee, United States of America
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Amy C. Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, Connecticut, United States of America
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, Connecticut, United States of America
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Rentsch CT, Morford KL, Fiellin DA, Bryant KJ, Justice AC, Tate JP. Safety of Gabapentin Prescribed for Any Indication in a Large Clinical Cohort of 571,718 US Veterans with and without Alcohol Use Disorder. Alcohol Clin Exp Res 2020; 44:1807-1815. [PMID: 32628784 PMCID: PMC7540277 DOI: 10.1111/acer.14408] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 06/18/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND Gabapentin is prescribed for seizures and pain and has efficacy for treating alcohol use disorder (AUD) starting at doses of 900 milligrams per day (mg/d). Recent evidence suggests safety concerns associated with gabapentin including adverse neurologic effects. Individuals with hepatitis C (HCV), HIV, or AUD may be at increased risk due to comorbidities and potential medication interactions. METHODS We identified patients prescribed gabapentin for ≥ 60 days for any indication between 2002 and 2015. We propensity-score matched each gabapentin-exposed patient with up to 5 gabapentin-unexposed patients. We followed patients for 2 years or until diagnosed with (i) falls or fractures, or (ii) altered mental status using validated ICD-9 diagnostic codes. We used Poisson regression to estimate incidence rates and relative risk (RR) of these adverse events in association with gabapentin exposure overall and stratified by age, race/ethnicity, sex, HCV, HIV, AUD, and dose. RESULTS Incidence of falls or fractures was 1.81 per 100 person-years (PY) among 140,310 gabapentin-exposed and 1.34/100 PY among 431,408 gabapentin-unexposed patients (RR 1.35, 95% confidence interval [CI] 1.28 to 1.44). Incidence of altered mental status was 1.08/100 PY among exposed and 0.97/100 PY among unexposed patients, RR of 1.12 (95% CI 1.04 to 1.20). Excess risk of falls or fractures associated with gabapentin exposure was observed in all subgroups except patients with HCV, HIV, or AUD; however, these groups had elevated incidence regardless of exposure. There was a clear dose-response relationship for falls or fractures with highest risk observed among those prescribed ≥ 2,400 mg/d (RR 1.90, 95% CI 1.50 to 2.40). Patients were at increased risk for altered mental status at doses 600 to 2,399 mg/d; however, low number of events in the highest dose category limited power to detect a statistically significant association ≥ 2,400 mg/d. CONCLUSIONS Gabapentin is associated with falls or fractures and altered mental status. Clinicians should be monitoring gabapentin safety, especially at doses ≥ 600 mg/d, in patients with and without AUD.
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Affiliation(s)
- Christopher T. Rentsch
- Faculty of Epidemiology & Population HealthLondon School of Hygiene & Tropical MedicineLondonUK
- Veterans Aging Cohort Study Coordinating CenterVA Connecticut Healthcare SystemWest HavenConnecticutUSA
| | - Kenneth L. Morford
- Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
| | - David A. Fiellin
- Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
- Center for Interdisciplinary Research on AIDSYale School of Public HealthNew HavenConnecticutUSA
| | - Kendall J. Bryant
- Director of HIV/AIDS ResearchNational Institute on Alcohol Abuse and AlcoholismBethesdaMarylandUSA
| | - Amy C. Justice
- Veterans Aging Cohort Study Coordinating CenterVA Connecticut Healthcare SystemWest HavenConnecticutUSA
- Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
- Center for Interdisciplinary Research on AIDSYale School of Public HealthNew HavenConnecticutUSA
| | - Janet P. Tate
- Veterans Aging Cohort Study Coordinating CenterVA Connecticut Healthcare SystemWest HavenConnecticutUSA
- Department of Internal MedicineYale School of MedicineNew HavenConnecticutUSA
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28
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Edelman EJ, Maisto SA, Hansen NB, Cutter CJ, Dziura J, Deng Y, Fiellin LE, O'Connor PG, Bedimo R, Gibert CL, Marconi VC, Rimland D, Rodriguez-Barradas MC, Simberkoff MS, Tate JP, Justice AC, Bryant KJ, Fiellin DA. Integrated stepped alcohol treatment for patients with HIV and at-risk alcohol use: a randomized trial. Addict Sci Clin Pract 2020; 15:28. [PMID: 32727618 PMCID: PMC7388231 DOI: 10.1186/s13722-020-00200-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 07/09/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND At-risk levels of alcohol use threaten the health of patients with HIV (PWH), yet evidence-based strategies to decrease alcohol use and improve HIV-related outcomes in this population are lacking. We examined the effectiveness of integrated stepped alcohol treatment (ISAT) on alcohol use and HIV outcomes among PWH and at-risk alcohol use. METHODS In this multi-site, randomized trial conducted between January 28, 2013 through July 14, 2017, we enrolled PWH and at-risk alcohol use [defined as alcohol consumption of ≥ 14 drinks per week or ≥ 4 drinks per occasion in men ≤ 65 years old or ≥ 7 drinks per week or ≥ 3 drinks per occasion in women or men > 65 years old]. ISAT (n = 46) involved: Step 1- Brief Negotiated Interview with telephone booster, Step 2- Motivational Enhancement Therapy, and Step 3- Addiction Physician Management. Treatment as usual (TAU) (n = 47) involved receipt of a health handout plus routine care. Analyses were conducted based on intention to treat principles. RESULTS Despite a multi-pronged approach, we only recruited 37% of the target population (n = 93/254). Among ISAT participants, 50% advanced to Step 2, among whom 57% advanced to Step 3. Participants randomized to ISAT and TAU had no observed difference in drinks per week over the past 30 days at week 24 (primary outcome) [least square means (Ls mean) (95% CI) = 8.8 vs. 10.6; adjusted mean difference (AMD) (95% CI) = - 0.4 (- 3.9, 3.0)]. CONCLUSION An insufficient number of patients were interested in participating in the trial. Efforts to enhance motivation of PWH with at-risk alcohol use to engage in alcohol-related research and build upon ISAT are needed. Trial registration Clinicaltrials.gov: NCT01410123, First posted August 4, 2011.
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Affiliation(s)
- E Jennifer Edelman
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA. .,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06510, USA.
| | | | - Nathan B Hansen
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06510, USA.,College of Public Health, University of Georgia, Athens, GA, 30602, USA
| | | | - James Dziura
- Yale Center for Analytic Sciences, Yale University School of Public Health, New Haven, CT, 06511, USA
| | - Yanhong Deng
- Yale Center for Analytic Sciences, Yale University School of Public Health, New Haven, CT, 06511, USA
| | - Lynn E Fiellin
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06510, USA
| | - Patrick G O'Connor
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA
| | - Roger Bedimo
- Veterans Affairs North Texas Health Care System and UT Southwestern, Dallas, TX, 75216, USA
| | - Cynthia L Gibert
- D.C. VAMC and George, Washington University School of Medicine and Health Sciences, Washington, D.C, 20422, USA
| | - Vincent C Marconi
- Atlanta VAMC and Emory University School of Medicine, Atlanta, GA, 30033, USA
| | - David Rimland
- Atlanta VAMC and Emory University School of Medicine, Atlanta, GA, 30033, USA
| | | | - Michael S Simberkoff
- VA NY Harbor Healthcare System and New York University School of Medicine, New York, NY, 10010, USA
| | - Janet P Tate
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA.,VA Connecticut Healthcare System, Veterans Aging Cohort Study, West Haven, CT, 06516, USA
| | - Amy C Justice
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA.,VA Connecticut Healthcare System, Veterans Aging Cohort Study, West Haven, CT, 06516, USA
| | - Kendall J Bryant
- National Institute On Alcohol Abuse and Alcoholism HIV/AIDS Program, Bethesda, MD, 20892-7003, USA
| | - David A Fiellin
- Yale School of Medicine, 367 Cedar Street, ESH A, New Haven, CT, 06510, USA.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06510, USA
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29
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Rodriguez-Barradas MC, McGinnis KA, Akgün K, Tate JP, Brown ST, Butt AA, Fine M, Goetz MB, Graber CJ, Huang L, Rimland D, Justice A, Crothers K. Validation for using electronic health records to identify community acquired pneumonia hospitalization among people with and without HIV. Pneumonia (Nathan) 2020; 12:6. [PMID: 32724760 PMCID: PMC7382068 DOI: 10.1186/s41479-020-00068-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Accepted: 06/07/2020] [Indexed: 02/06/2023] Open
Abstract
Background Cohort studies identifying the incidence, complications and co-morbidities associated with community acquired pneumonia (CAP) are largely based on administrative datasets and rely on International Classification of Diseases (ICD) codes; however, the reliability of ICD codes for hospital admissions for CAP in people with HIV (PWH) has not been systematically assessed. Methods We used data from the Veterans Aging Cohort Study survey sample (N = 6824; 3410 PWH and 3414 uninfected) to validate the use of electronic health records (EHR) data to identify CAP hospitalizations when compared to chart review and to compare the performance in PWH vs. uninfected patients. We used different EHR algorithms that included a broad set of CAP ICD-9 codes, a set restricted to bacterial and viral CAP codes, and algorithms that included pharmacy data and/or other ICD-9 diagnoses frequently associated with CAP. We also compared microbiologic workup and etiologic diagnosis by HIV status among those with CAP. Results Five hundred forty-nine patients were identified as having an ICD-9 code compatible with a CAP diagnosis (13% of PWH and 4% of the uninfected, p < 0.01). The EHR algorithm with the best overall positive predictive value (82%) was obtained by using the restricted set of ICD-9 codes (480-487) in primary position or secondary only to selected codes as primary (HIV disease, respiratory failure, sepsis or bacteremia) with the addition of EHR pharmacy data; this algorithm yielded PPVs of 83% in PWH and 73% in uninfected (P = 0.1) groups. Adding aspiration pneumonia (ICD-9 code 507) to any of the ICD-9 code/pharmacy combinations increased the number of cases but decreased the overall PPV. Allowing COPD exacerbation in the primary position improved the PPV among the uninfected group only (to 76%). More PWH than uninfected patients underwent microbiologic evaluation or had respiratory samples submitted. Conclusions ICD-9 code-based algorithms perform similarly to identify CAP in PLWH and uninfected individuals. Adding antimicrobial use data and allowing as primary diagnoses ICD-9 codes frequently used in patients with CAP improved the performance of the algorithms in both groups of patients. The algorithms consistently performed better among PWH.
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Affiliation(s)
| | | | - Kathleen Akgün
- VA Connecticut Healthcare System, West Haven, CT USA.,Yale University, New Haven, CT USA
| | - Janet P Tate
- VA Connecticut Healthcare System, West Haven, CT USA.,Yale University, New Haven, CT USA
| | - Sheldon T Brown
- James J Peters VAMC, Bronx, NY USA.,Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Adeel A Butt
- VA Pittsburgh Healthcare System, Pittsburgh, PA USA.,Weill Cornell Medical College, New York, NY USA.,Weill Cornell Medical College, Doha, Qatar
| | - Michael Fine
- VA Pittsburgh Healthcare System, Pittsburgh, PA USA
| | - Matthew Bidwell Goetz
- VA Greater Los Angeles Healthcare System, and David Geffen School of Medicine at UCLA, Los Angeles, CA USA
| | - Christopher J Graber
- VA Greater Los Angeles Healthcare System, and David Geffen School of Medicine at UCLA, Los Angeles, CA USA
| | - Laurence Huang
- San Francisco General Hospital and University of California San Francisco, San Francisco, CA USA
| | - David Rimland
- VAMC and Emory University School of Medicine, Atlanta, GA USA
| | - Amy Justice
- VA Connecticut Healthcare System, West Haven, CT USA.,Yale University, New Haven, CT USA
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Do A, Esserman DA, Krishnan S, Lim JK, Taddei TH, Hauser RG, Tate JP, Re VL, Justice AC. Excess Weight Gain After Cure of Hepatitis C Infection with Direct-Acting Antivirals. J Gen Intern Med 2020; 35:2025-2034. [PMID: 32342483 PMCID: PMC7352003 DOI: 10.1007/s11606-020-05782-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 03/06/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Cure from chronic hepatitis C virus (HCV) infection is readily achievable with direct-acting antivirals (DAA), but little is known about optimal management after treatment. Weight gained after DAA treatment may mitigate benefits or increase risk for liver disease progression. As the single largest sample of HCV-infected individuals receiving DAA treatment in the United States, the Veterans Affairs (VA) Birth Cohort is an ideal setting to assess weight gain after DAA treatment. METHODS We performed a prospective study of patients dispensed DAA therapy from January 2014 to June 2015. Weight change was calculated as the difference in weight from sustained virologic response (SVR) determination to 2 years later. Demographic, weight, height, prescription, laboratory, and diagnosis code data were used for covariate definitions. We used multiple logistic regression to assess the association between candidate predictors and excess weight gain (≥ 10 lbs) after 2 years. RESULTS Among 11,469 patients, 78.0% of patients were already overweight or obese at treatment initiation. Overall, SVR was achieved in 97.0% of patients. After 2 years, 52.6% of patients gained weight and 19.8% gained excess weight. In those with SVR, weight gain was as high as 38.2 lbs, with the top 10% gaining ≥ 16.5 lbs. Only 1% of those with obesity at treatment initiation normalized their weight class after 2 years. Significant predictors of post-SVR weight gain were SVR achievement, lower age, high FIB-4 score, cirrhosis, and weight class at treatment initiation. CONCLUSION Weight gain is common after DAA treatment, even among those who are overweight or obese prior to treatment. Major predictors include age, baseline weight, alcohol, cirrhosis, and SVR. Everyone receiving DAAs should be counseled against weight gain with a particular emphasis among those at higher risk.
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Affiliation(s)
- Albert Do
- Section of Digestive Diseases, Department of Internal Medicine , Yale University School of Medicine, 333 Cedar St, 1080 LMP, New Haven, CT, 06510, USA.
| | - Denise A Esserman
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, USA
| | - Supriya Krishnan
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Joseph K Lim
- Section of Digestive Diseases, Department of Internal Medicine , Yale University School of Medicine, 333 Cedar St, 1080 LMP, New Haven, CT, 06510, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Tamar H Taddei
- Section of Digestive Diseases, Department of Internal Medicine , Yale University School of Medicine, 333 Cedar St, 1080 LMP, New Haven, CT, 06510, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Ronald G Hauser
- VA Connecticut Healthcare System, West Haven, CT, USA
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, USA
| | - Janet P Tate
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania University of Pennsylvania, Philadelphia, PA, USA
- Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy C Justice
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
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Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King JT, Skanderson M, Hauser RG, Schultze A, Jarvis CI, Holodniy M, Re VL, Akgün KM, Crothers K, Taddei TH, Freiberg MS, Justice AC. Covid-19 by Race and Ethnicity: A National Cohort Study of 6 Million United States Veterans. medRxiv 2020. [PMID: 32511524 DOI: 10.1101/2020.05.12.20099135.] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of morbidity and mortality from symptomatic SARS-Cov-2 infection or coronavirus disease 2019 (Covid-19). Most studies investigating racial and ethnic disparities to date have focused on hospitalized patients or have not characterized who received testing or those who tested positive for Covid-19. OBJECTIVE To compare patterns of testing and test results for coronavirus 2019 (Covid-19) and subsequent mortality by race and ethnicity in the largest integrated healthcare system in the United States. DESIGN Retrospective cohort study. SETTING United States Department of Veterans Affairs (VA). PARTICIPANTS 5,834,543 individuals in care, among whom 62,098 were tested and 5,630 tested positive for Covid-19 between February 8 and May 4, 2020. Exposures: Self-reported race/ethnicity. MAIN OUTCOME MEASURES We evaluated associations between race/ethnicity and receipt of Covid-19 testing, a positive test result, and 30-day mortality, accounting for a wide range of demographic and clinical risk factors including comorbid conditions, site of care, and urban versus rural residence. RESULTS Among all individuals in care, 74% were non-Hispanic white (white), 19% non-Hispanic black (black), and 7% Hispanic. Compared with white individuals, black and Hispanic individuals were more likely to be tested for Covid-19 (tests per 1000: white=9.0, [95% CI 8.9 to 9.1]; black=16.4, [16.2 to 16.7]; and Hispanic=12.2, [11.9 to 12.5]). While individuals from minority backgrounds were more likely to test positive (black vs white: OR 1.96, 95% CI 1.81 to 2.12; Hispanic vs white: OR 1.73, 95% CI 1.53 to 1.96), 30-day mortality did not differ by race/ethnicity (black vs white: OR 0.93, 95% CI 0.64 to 1.33; Hispanic vs white: OR 1.07, 95% CI 0.61 to 1.87). CONCLUSIONS Black and Hispanic individuals are experiencing an excess burden of Covid-19 not entirely explained by underlying medical conditions or where they live or receive care. While there was no observed difference in mortality by race or ethnicity, our findings may underestimate risk in the broader US population as health disparities tend to be reduced in VA.
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Affiliation(s)
- Christopher T Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Lesley S Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Neurosurgery, Yale School of Medicine, New Haven, CT, US, 06520
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
| | - Ronald G Hauser
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Anna Schultze
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Christopher I Jarvis
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Mark Holodniy
- VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, US, 94304.,Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine and Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US, 19104
| | - Kathleen M Akgün
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Kristina Crothers
- VA Puget Sound Health Care System and Department of Medicine, University of Washington School of Medicine, Seattle, WA, US, 98104
| | - Tamar H Taddei
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Matthew S Freiberg
- Geriatric Research Education and Clinical Center (GRECC), US Department of Veterans Affairs, Tennessee Valley Health Care System, Nashville, TN, US 37212.,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, US, 37232
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.,Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, US, 06511
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Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King JT, Skanderson M, Hauser RG, Schultze A, Jarvis CI, Holodniy M, Re VL, Akgün KM, Crothers K, Taddei TH, Freiberg MS, Justice AC. Covid-19 by Race and Ethnicity: A National Cohort Study of 6 Million United States Veterans. medRxiv 2020:2020.05.12.20099135. [PMID: 32511524 PMCID: PMC7273292 DOI: 10.1101/2020.05.12.20099135] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of morbidity and mortality from symptomatic SARS-Cov-2 infection or coronavirus disease 2019 (Covid-19). Most studies investigating racial and ethnic disparities to date have focused on hospitalized patients or have not characterized who received testing or those who tested positive for Covid-19. OBJECTIVE To compare patterns of testing and test results for coronavirus 2019 (Covid-19) and subsequent mortality by race and ethnicity in the largest integrated healthcare system in the United States. DESIGN Retrospective cohort study. SETTING United States Department of Veterans Affairs (VA). PARTICIPANTS 5,834,543 individuals in care, among whom 62,098 were tested and 5,630 tested positive for Covid-19 between February 8 and May 4, 2020. Exposures: Self-reported race/ethnicity. MAIN OUTCOME MEASURES We evaluated associations between race/ethnicity and receipt of Covid-19 testing, a positive test result, and 30-day mortality, accounting for a wide range of demographic and clinical risk factors including comorbid conditions, site of care, and urban versus rural residence. RESULTS Among all individuals in care, 74% were non-Hispanic white (white), 19% non-Hispanic black (black), and 7% Hispanic. Compared with white individuals, black and Hispanic individuals were more likely to be tested for Covid-19 (tests per 1000: white=9.0, [95% CI 8.9 to 9.1]; black=16.4, [16.2 to 16.7]; and Hispanic=12.2, [11.9 to 12.5]). While individuals from minority backgrounds were more likely to test positive (black vs white: OR 1.96, 95% CI 1.81 to 2.12; Hispanic vs white: OR 1.73, 95% CI 1.53 to 1.96), 30-day mortality did not differ by race/ethnicity (black vs white: OR 0.93, 95% CI 0.64 to 1.33; Hispanic vs white: OR 1.07, 95% CI 0.61 to 1.87). CONCLUSIONS Black and Hispanic individuals are experiencing an excess burden of Covid-19 not entirely explained by underlying medical conditions or where they live or receive care. While there was no observed difference in mortality by race or ethnicity, our findings may underestimate risk in the broader US population as health disparities tend to be reduced in VA.
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Affiliation(s)
- Christopher T Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Lesley S Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, US, 06520
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
| | - Ronald G Hauser
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Anna Schultze
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Christopher I Jarvis
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Mark Holodniy
- VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, US, 94304
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine and Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US, 19104
| | - Kathleen M Akgün
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Kristina Crothers
- VA Puget Sound Health Care System and Department of Medicine, University of Washington School of Medicine, Seattle, WA, US, 98104
| | - Tamar H Taddei
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Matthew S Freiberg
- Geriatric Research Education and Clinical Center (GRECC), US Department of Veterans Affairs, Tennessee Valley Health Care System, Nashville, TN, US 37212
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, US, 37232
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, US, 06511
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Edelman EJ, Li Y, Barry D, Braden JB, Crystal S, Kerns RD, Gaither JR, Gordon KS, Manhapra A, Merlin JS, Moore BA, Oldfield BJ, Park LS, Rentsch CT, Skanderson M, Williams EC, Justice AC, Tate JP, Becker WC, Marshall BD. Trajectories of Self-Reported Opioid Use Among Patients With HIV Engaged in Care: Results From a National Cohort Study. J Acquir Immune Defic Syndr 2020; 84:26-36. [PMID: 32267658 PMCID: PMC7147724 DOI: 10.1097/qai.0000000000002310] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND No prior studies have characterized long-term patterns of opioid use regardless of source or reason for use among patients with HIV (PWH). We sought to identify trajectories of self-reported opioid use and their correlates among a national sample of PWH engaged in care. SETTING Veterans Aging Cohort Study, a prospective cohort including PWH receiving care at 8 US Veterans Health Administration (VA) sites. METHODS Between 2002 and 2018, we assessed past year opioid use frequency based on self-reported "prescription painkillers" and/or heroin use at baseline and follow-up. We used group-based trajectory models to identify opioid use trajectories and multinomial logistic regression to determine baseline factors independently associated with escalating opioid use compared to stable, infrequent use. RESULTS Among 3702 PWH, we identified 4 opioid use trajectories: (1) no lifetime use (25%); (2) stable, infrequent use (58%); (3) escalating use (7%); and (4) de-escalating use (11%). In bivariate analysis, anxiety; pain interference; prescribed opioids, benzodiazepines and gabapentinoids; and marijuana use were associated with escalating opioid group membership compared to stable, infrequent use. In multivariable analysis, illness severity, pain interference, receipt of prescribed benzodiazepine medications, and marijuana use were associated with escalating opioid group membership compared to stable, infrequent use. CONCLUSION Among PWH engaged in VA care, 1 in 15 reported escalating opioid use. Future research is needed to understand the impact of psychoactive medications and marijuana use on opioid use and whether enhanced uptake of evidence-based treatment of pain and psychiatric symptoms can prevent escalating use among PWH.
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Affiliation(s)
- E. Jennifer Edelman
- Yale School of Medicine, New Haven, CT
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT
| | - Yu Li
- Brown University School of Public Health, Providence, RI
| | | | - Jennifer Brennan Braden
- University of Washington School of Medicine, Seattle, WA
- Valley Medical Center Psychiatry and Counseling, Behavioral Health Integration Program
| | - Stephen Crystal
- Center for Health Services Research, Institute for Health, Rutgers University, Rutgers, NJ
| | - Robert D. Kerns
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | | | - Kirsha S. Gordon
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | - Ajay Manhapra
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | | | - Brent A. Moore
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | | | | | - Christopher T. Rentsch
- VA Connecticut Healthcare System, West Haven, CT
- London School of Hygiene and Tropical Medicine, London, UK
| | | | - Emily C. Williams
- VA Puget Sound Health Services Research and Development and Department of Health Services, University of Washington, Seattle, WA
| | - Amy C. Justice
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | - Janet P. Tate
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | - William C. Becker
- Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
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Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King JT, Skanderson M, Hauser RG, Schultze A, Jarvis CI, Holodniy M, Re VL, Akgün KM, Crothers K, Taddei TH, Freiberg MS, Justice AC. Covid-19 Testing, Hospital Admission, and Intensive Care Among 2,026,227 United States Veterans Aged 54-75 Years. medRxiv 2020:2020.04.09.20059964. [PMID: 32511595 PMCID: PMC7276022 DOI: 10.1101/2020.04.09.20059964] [Citation(s) in RCA: 303] [Impact Index Per Article: 75.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes coronavirus disease 2019 (Covid-19), an evolving pandemic. Limited data are available characterizing SARS-Cov-2 infection in the United States. OBJECTIVE To determine associations between demographic and clinical factors and testing positive for coronavirus 2019 (Covid-19+), and among Covid-19+ subsequent hospitalization and intensive care. DESIGN, SETTING, AND PARTICIPANTS Retrospective cohort study including all patients tested for Covid-19 between February 8 and March 30, 2020, inclusive. We extracted electronic health record data from the national Veterans Affairs Healthcare System, the largest integrated healthcare system in the United States, on 2,026,227 patients born between 1945 and 1965 and active in care. Exposures: Demographic data, comorbidities, medication history, substance use, vital signs, and laboratory measures. Laboratory tests were analyzed first individually and then grouped into a validated summary measure of physiologic injury (VACS Index). Main Outcomes and Measures: We evaluated which factors were associated with Covid-19+ among all who tested. Among Covid-19+ we identified factors associated with hospitalization or intensive care. We identified independent associations using multivariable and conditional multivariable logistic regression with multiple imputation of missing values. RESULTS Among Veterans aged 54-75 years, 585/3,789 (15.4%) tested Covid-19+. In adjusted analysis (C-statistic=0.806) black race was associated with Covid-19+ (OR 4.68, 95% CI 3.79-5.78) and the association remained in analyses conditional on site (OR 2.56, 95% CI 1.89-3.46). In adjusted models, laboratory abnormalities (especially fibrosis-4 score [FIB-4] >3.25 OR 8.73, 95% CI 4.11-18.56), and VACS Index (per 5-point increase OR 1.62, 95% CI 1.43-1.84) were strongly associated with hospitalization. Associations were similar for intensive care. Although significant in unadjusted analyses, associations with comorbid conditions and medications were substantially reduced and, in most cases, no longer significant after adjustment. CONCLUSIONS AND RELEVANCE Black race was strongly associated with Covid-19+, but not with hospitalization or intensive care. Among Covid-19+, risk of hospitalization and intensive care may be better characterized by laboratory measures and vital signs than by comorbid conditions or prior medication exposure.
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Affiliation(s)
- Christopher T Rentsch
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Farah Kidwai-Khan
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Janet P Tate
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Lesley S Park
- Stanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Joseph T King
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, US, 06520
| | - Melissa Skanderson
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
| | - Ronald G Hauser
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Anna Schultze
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Christopher I Jarvis
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT
| | - Mark Holodniy
- VA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, US, 94304
- Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, CA, US, 94305
| | - Vincent Lo Re
- Division of Infectious Diseases, Department of Medicine and Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US, 19104
| | - Kathleen M Akgün
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Kristina Crothers
- VA Puget Sound Health Care System and Department of Medicine, University of Washington School of Medicine, Seattle, WA, US, 98104
| | - Tamar H Taddei
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
| | - Matthew S Freiberg
- Geriatric Research Education and Clinical Center (GRECC), US Department of Veterans Affairs, Tennessee Valley Health Care System, Nashville, TN, US 37212
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, US, 37232
| | - Amy C Justice
- VA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US, 06520
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, US, 06511
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Gordon KS, McGinnis K, Dao C, Rentsch CT, Small A, Smith RV, Kember RL, Gelernter J, Kranzler HR, Bryant KJ, Tate JP, Justice AC. Differentiating Types of Self-Reported Alcohol Abstinence. AIDS Behav 2020; 24:655-665. [PMID: 31435887 DOI: 10.1007/s10461-019-02638-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
We contrast three types of abstinence: quit after alcohol associated problems (Q-AP), quit for other reasons (Q-OR), and lifetime abstainer (LTA). We summarized the characteristics of people living with HIV (PLWH), and matched uninfected individuals, by levels of alcohol use and types of abstinence. We then identified factors that differentiate abstinence and determined whether the association with an alcohol biomarker or a genetic polymorphism is improved by differentiating abstinence. Among abstainers, 34% of PLWH and 38% of uninfected were Q-AP; 53% and 53% were Q-OR; and 12% and 10% were LTA. Logistic regression models found smoking, alcohol, cocaine, and hepatitis C increased odds of Q-AP, whereas smoking and marijuana decreased odds of LTA. Differentiating types of abstinence improved association. Q-APs and LTAs can be readily differentiated by an alcohol biomarker and genetic polymorphism. Differentiating type of abstinence may enhance understanding of alcohol health effects.
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Affiliation(s)
- Kirsha S Gordon
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA.
- Yale University School of Medicine, New Haven, CT, 06510, USA.
| | - Kathleen McGinnis
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
| | - Cecilia Dao
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Christopher T Rentsch
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK
| | - Aeron Small
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | | | - Rachel L Kember
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Corporal Michael J. Crescenz Veterans Affairs Medical Center VISN4 MIRECC, Philadelphia, PA, 19104, USA
| | - Joel Gelernter
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Henry R Kranzler
- Corporal Michael J. Crescenz Veterans Affairs Medical Center VISN4 MIRECC, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Kendall J Bryant
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, 20892, USA
| | - Janet P Tate
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, 11ACSL-G, 950 Campbell Avenue, West Haven, CT, 06516, USA
- Yale University School of Medicine, New Haven, CT, 06510, USA
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36
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Rentsch CT, Edelman EJ, Justice AC, Marshall BDL, Xu K, Smith AH, Crystal S, Gaither JR, Gordon AJ, Smith RV, Kember RL, Polimanti R, Gelernter J, Fiellin DA, Tate JP, Kranzler HR, Becker WC. Patterns and Correlates of Prescription Opioid Receipt Among US Veterans: A National, 18-Year Observational Cohort Study. AIDS Behav 2019; 23:3340-3349. [PMID: 31317364 PMCID: PMC7344341 DOI: 10.1007/s10461-019-02608-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
A better understanding of predisposition to transition to high-dose, long-term opioid therapy after initial opioid receipt could facilitate efforts to prevent opioid use disorder (OUD). We extracted data on 69,268 patients in the Veterans Aging Cohort Study who received any opioid prescription between 1998 and 2015. Using latent growth mixture modelling, we identified four distinguishable dose trajectories: low (53%), moderate (29%), escalating (13%), and rapidly escalating (5%). Compared to low dose trajectory, those in the rapidly escalating dose trajectory were proportionately more European-American (59% rapidly escalating vs. 38% low); had a higher prevalence of HIV (31% vs. 29%) and hepatitis C (18% vs. 12%); and during follow-up, had a higher incidence of OUD diagnoses (13% vs. 3%); were hospitalised more often [18.1/100 person-years (PYs) vs. 12.5/100 PY]; and had higher all-cause mortality (4.7/100 PY vs. 1.8/100 PY, all p < 0.0001). These measures can potentially be used in future prevention research, including genetic discovery.
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Affiliation(s)
- Christopher T Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
- Veterans Aging Cohort Study Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA.
| | - E Jennifer Edelman
- Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06515, USA
| | - Amy C Justice
- Veterans Aging Cohort Study Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA
- Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06515, USA
| | - Brandon D L Marshall
- Department of Epidemiology, Brown School of Public Health, Providence, RI, 02903, USA
| | - Ke Xu
- Department of Psychiatry, Yale School of Medicine and VA Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Andrew H Smith
- Department of Psychiatry, Yale School of Medicine and VA Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Stephen Crystal
- Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Julie R Gaither
- Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, 06515, USA
- Pain Research, Informatics, Multi-morbidities and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Adam J Gordon
- VA COIN Informatics, Decision-Enhancement and Analytic Sciences Center, Salt Lake City VA Health Care System, University of Utah School of Medicine, Salt Lake City, UT, 84132, USA
| | - Rachel V Smith
- School of Nursing, University of Louisville, Louisville, KY, 40202, USA
| | - Rachel L Kember
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine and VA Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine and VA Connecticut Healthcare System, West Haven, CT, 06516, USA
- Departments of Genetics and Neuroscience, Yale School of Medicine, New Haven, CT, 06515, USA
| | - David A Fiellin
- Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, 06515, USA
| | - Janet P Tate
- Veterans Aging Cohort Study Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA
- Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center, Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - William C Becker
- Internal Medicine, Yale School of Medicine, New Haven, CT, 06515, USA
- Pain Research, Informatics, Multi-morbidities and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, 06516, USA
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McGinnis KA, Fiellin DA, Skanderson M, Hser YI, Lucas GM, Justice AC, Tate JP. Opioid use trajectory groups and changes in a physical health biomarker among HIV-positive and uninfected patients receiving opioid agonist treatment. Drug Alcohol Depend 2019; 204:107511. [PMID: 31546119 PMCID: PMC6993986 DOI: 10.1016/j.drugalcdep.2019.06.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 05/31/2019] [Accepted: 06/03/2019] [Indexed: 12/31/2022]
Abstract
BACKGROUND Objective outcomes for measuring the physical health effects of substance use disorder treatment are needed. We compared the responsiveness of CD4, HIV-1 RNA and a biomarker index (VACS Index 2.0) to changes in opioid use among people with HIV (PWH) and uninfected individuals receiving opioid agonist treatment (OAT). METHODS Electronic health record data were used to identify patients who received ≥90 days of OAT and had ≥1 urine toxicology test in the Veterans Aging Cohort Study. Trajectory models identified patterns of opioid urine toxicology results. We used linear regression adjusted for age and race/ethnicity to determine associations between opioid toxicology groups and biomarker changes from up to one-year pre OAT to 3-15 months after OAT initiation. RESULTS Among 266 with detectable HIV-1 RNA, 366 with suppressed HIV-1 RNA, and 1183 uninfected patients, we identified five opioid toxicology groups ranging from consistently negative (54%) to consistently positive (9%). Among PWH with detectable HIV-1 RNA, all three biomarkers improved more for those consistently negative compared to those consistently positive (all p < .05). Among PWH with suppressed HIV-1 RNA, CD4 improved for those consistently negative; and worsened for those in the slow decrease toward negative group (p = .04). Among those uninfected, VACS Index 2.0 did not differ by opioid toxicology groups. CONCLUSIONS Among patients on OAT, changes in biomarkers are associated with opioid toxicology groups among PWH, but vary by HIV-1 RNA. These findings may be useful for measuring the health effects of OAT.
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Affiliation(s)
| | - David A Fiellin
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | | | - Yih-Ing Hser
- Integrated Substance Abuse Programs, Univeristy of California Los Angeles, Los Angeles, CA, USA
| | - Gregory M Lucas
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Amy C Justice
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA; Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Janet P Tate
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA; Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
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Hanberg JS, Freiberg MS, Goetz MB, Rodriguez-Barradas MC, Gibert C, Oursler KA, Justice AC, Tate JP. Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios as Prognostic Inflammatory Biomarkers in Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV), and HIV/HCV Coinfection. Open Forum Infect Dis 2019; 6:ofz347. [PMID: 31660334 PMCID: PMC6786514 DOI: 10.1093/ofid/ofz347] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 07/24/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Inflammation in human immunodeficiency virus (HIV)-infected patients is associated with poorer health outcomes. Whether inflammation as measured by the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) adds information to existing prognostic indices is not known. METHODS We analyzed data from 2000 to 2012 in the Veterans Aging Cohort Study (VACS), overall and stratified by HIV/hepatitis C virus status (n = 89 786). We randomly selected a visit date at which all laboratory values of interest were available within 180 days; participants with HIV received at least 1 year of antiretroviral therapy. We followed patients for (1) mortality and (2) hepatic decompensation (HD) and analyzed associations using Cox regression, adjusted for a validated mortality risk index (VACS Index 2.0). In VACS Biomarker Cohort, we considered correlation with biomarkers of inflammation: interleukin-6, D-dimer, and soluble CD-14. RESULTS Neutrophil-to-lymphocyte ratio and PLR demonstrated strong unadjusted associations with mortality (P < .0001) and HD (P < .0001) and were weakly correlated with other inflammatory biomarkers. Although NLR remained statistically independent for mortality, as did PLR for HD, the addition of NLR and PLR to the VACS Index 2.0 did not result in significant improvement in discrimination compared with VACS Index 2.0 alone for mortality (C-statistic 0.767 vs 0.758) or for HD (C-statistic 0.805 vs 0.801). CONCLUSIONS Neutrophil-to-lymphocyte ratio and PLR were strongly associated with mortality and HD and weakly correlated with inflammatory biomarkers. However, most of their association was explained by VACS Index 2.0. Addition of NLR and PLR to VACS 2.0 did not substantially improve discrimination for either outcome.
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Affiliation(s)
- Jennifer S Hanberg
- Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
| | - Matthew S Freiberg
- Department of Medicine and Epidemiology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Matthew B Goetz
- Division of Infectious Diseases, University of California, David Geffen School of Medicine, Los Angeles
- Greater Los Angeles VA Healthcare Center, California
| | - Maria C Rodriguez-Barradas
- Department of Medicine and Infectious Disease, Baylor College of Medicine, Houston, Texas
- Michael E. DeBakey VA Medical Center, Houston, Texas
| | - Cynthia Gibert
- Division of Infectious Diseases and Medicine, George Washington University, School of Medicine and Health Sciences, Washington, District of Columbia
| | - Kris Ann Oursler
- Department of Medicine, Virginia Tech Carilion School of Medicine, Salem
- University of Maryland School of Medicine, Baltimore
| | - Amy C Justice
- Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
| | - Janet P Tate
- Department of Medicine, Yale University School of Medicine, New Haven, Connecticut
- VA Connecticut Healthcare System, West Haven
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Kranzler HR, Zhou H, Kember RL, Smith RV, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Author Correction: Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 2019; 10:4050. [PMID: 31481659 PMCID: PMC6722074 DOI: 10.1038/s41467-019-11916-0] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Affiliation(s)
- Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. .,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.
| | - Hang Zhou
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Rachel L Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Rachel Vickers Smith
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.,University of Louisville School of Nursing, Louisville, KY, 40202, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA.,Yale School of Public Health, New Haven, CT, 06511, USA
| | - Scott Damrauer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA.,Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Derek Klarin
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Jeffrey Reid
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - John Overton
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Daniel J Rader
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Zhongshan Cheng
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - William C Becker
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - John Concato
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Ke Xu
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Renato Polimanti
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Hongyu Zhao
- Yale School of Medicine, New Haven, CT, 06511, USA.,Yale School of Public Health, New Haven, CT, 06511, USA
| | - Joel Gelernter
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
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McGinnis KA, Justice AC, Tate JP, Kranzler HR, Tindle HA, Becker WC, Concato J, Gelernter J, Li B, Zhang X, Zhao H, Crothers K, Xu K. Using DNA methylation to validate an electronic medical record phenotype for smoking. Addict Biol 2019; 24:1056-1065. [PMID: 30284751 DOI: 10.1111/adb.12670] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 05/22/2018] [Accepted: 07/22/2018] [Indexed: 12/14/2022]
Abstract
A validated, scalable approach to characterizing (phenotyping) smoking status is needed to facilitate genetic discovery. Using established DNA methylation sites from blood samples as a criterion standard for smoking behavior, we compare three candidate electronic medical record (EMR) smoking metrics based on longitudinal EMR text notes. With data from the Veterans Aging Cohort Study (VACS), we employed a validated algorithm to translate each smoking-related text note into current, past or never categories. We compared three alternative summary characterizations of smoking: most recent, modal and trajectories using descriptive statistics and Spearman's correlation coefficients. Logistic regression and area under the curve analyses were used to compare the associations of these phenotypes with the DNA methylation sites, cg05575921 and cg03636183, which are known to have strong associations with current smoking. DNA methylation data were available from the VACS Biomarker Cohort (VACS-BC), a sub-study of VACS. We also considered whether the associations differed by the certainty of trajectory group assignment (<0.80/≥0.80). Among 140 152 VACS participants, EMR summary smoking phenotypes varied in frequency by the metric chosen: current from 33 to 53 percent; past from 16 to 24 percent and never from 24 to 33 percent. The association between the EMR smoking pairs was highest for modal and trajectories (rho = 0.89). Among 728 individuals in the VACS-BC, both DNA methylation sites were associated with all three EMR summary metrics (p < 0.001), but the strongest association with both methylation sites was observed for trajectories (p < 0.001). Longitudinal EMR smoking data support using a summary phenotype, the validity of which is enhanced when data are integrated into statistical trajectories.
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Affiliation(s)
| | - Amy C. Justice
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
- Yale School of Public Health; New Haven CT USA
| | - Janet P. Tate
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Henry R. Kranzler
- VISN 4 MIRECC; Crescenz VAMC; Philadelphia PA USA
- University of Pennsylvania Perelman School of Medicine; Philadelphia PA USA
| | - Hilary A. Tindle
- Vanderbilt University Medical Center; Nashville TN USA
- Geriatric Research Education and Clinical Centers (GRECC), Veterans Affairs Tennessee Valley Healthcare System; Nashville TN USA
| | - William C. Becker
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - John Concato
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Joel Gelernter
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
- Yale School of Medicine; New Haven CT USA
| | - Boyang Li
- Yale School of Medicine; New Haven CT USA
| | | | - Hongyu Zhao
- Yale School of Medicine; New Haven CT USA
- Yale School of Public Health; New Haven CT USA
| | | | - Ke Xu
- Veterans Affairs Connecticut Healthcare System; West Haven CT USA
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Justice AC, Tate JP. Ageing with and without HIV: will advanced age bring equity or greater disparity? J Int AIDS Soc 2019; 22:e25400. [PMID: 31571414 PMCID: PMC6769376 DOI: 10.1002/jia2.25400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 09/10/2019] [Indexed: 11/21/2022] Open
Affiliation(s)
- Amy C Justice
- Veterans Affairs Connecticut Healthcare SystemWest HavenCTUSA
- School of MedicineYale UniversityNew HavenCTUSA
- School of Public HealthYale UniversityNew HavenCTUSA
| | - Janet P Tate
- Veterans Affairs Connecticut Healthcare SystemWest HavenCTUSA
- School of MedicineYale UniversityNew HavenCTUSA
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Edelman EJ, Maisto SA, Hansen NB, Cutter CJ, Dziura J, Deng Y, Fiellin LE, O'Connor PG, Bedimo R, Gibert CL, Marconi VC, Rimland D, Rodriguez-Barradas MC, Simberkoff MS, Tate JP, Justice AC, Bryant KJ, Fiellin DA. Integrated stepped alcohol treatment for patients with HIV and liver disease: A randomized trial. J Subst Abuse Treat 2019; 106:97-106. [PMID: 31540617 DOI: 10.1016/j.jsat.2019.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 08/07/2019] [Accepted: 08/08/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND There is no known safe level of alcohol use among patients with HIV and liver disease. We examined the effectiveness of integrated stepped alcohol treatment (ISAT) on alcohol use, HIV, and liver outcomes among patients with HIV and liver disease. METHODS In this multi-site, randomized trial conducted between January 28, 2013 through July 15, 2016, we enrolled 95 patients with HIV and liver disease [defined as having active hepatitis C infection or FIB-4 score > 1.45]. ISAT (n = 49) involved: Step 1- Brief Negotiated Interview with telephone booster, Step 2- Motivational Enhancement Therapy, and Step 3- Addiction Physician Management. Treatment as usual (TAU) (n = 46) involved receipt of a health handout plus routine care. Analyses were conducted based on intention to treat. RESULTS Among ISAT participants, 55% advanced to Step 2, among whom 70% advanced to Step 3. Participants randomized to ISAT and TAU increased abstinence (primary outcome) over time. Abstinence rates were non-significantly higher by self-report (38% vs. 23%, adjusted odds ratio [AOR] [95% CI] = 2.6 [0.8, 9.0]) and phosphatidylethanol (43% vs. 32%, AOR [95% CI] = 1.8 [0.5, 6.3] among those randomized to ISAT vs. TAU at week 24. VACS Index scores (AMD [95% CI] = 1.1 [-3.2, 5.5]) and the proportion with an undetectable HIV viral load (AOR [95% CI] = 0.3 [0.1, 1.3]) did not differ by group at week 24 (p values >0.05). ISAT had non-significantly lower FIB-4 scores (adjusted mean difference [AMD] [95% CI] = -0.2 [-0.9, 0.5]), ALT (AMD [95% CI] = -7 [-20, 7]) and AST (AMD [95% CI] = -4 [-15, 7]) at week 24 compared to TAU. CONCLUSION ISAT is feasible and potentially effective at enhancing delivery of evidence-based alcohol treatment to promote alcohol abstinence and improve liver biomarkers among patients with HIV and liver disease.
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Affiliation(s)
- E Jennifer Edelman
- Yale School of Medicine, New Haven, CT 06510, United States of America; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT 06510, United States of America.
| | - Stephen A Maisto
- Syracuse University, Syracuse, NY 13244, United States of America
| | - Nathan B Hansen
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT 06510, United States of America; College of Public Health, University of Georgia, Athens, GA 30602, United States of America
| | | | - James Dziura
- Yale Center for Analytic Sciences, Yale School of Public Health, New Haven, CT 06511, United States of America
| | - Yanhong Deng
- Yale Center for Analytic Sciences, Yale School of Public Health, New Haven, CT 06511, United States of America
| | - Lynn E Fiellin
- Yale School of Medicine, New Haven, CT 06510, United States of America; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT 06510, United States of America
| | | | - Roger Bedimo
- Veterans Affairs North Texas Health Care System, UT Southwestern, Dallas, TX 75216, United States of America
| | - Cynthia L Gibert
- D.C. VAMC, George Washington University School of Medicine and Health Sciences, Washington, DC 20422, United States of America
| | - Vincent C Marconi
- Atlanta VAMC, Emory University School of Medicine, Atlanta, GA 30033, United States of America
| | - David Rimland
- Atlanta VAMC, Emory University School of Medicine, Atlanta, GA 30033, United States of America
| | | | - Michael S Simberkoff
- VA NY Harbor Healthcare System, New York University School of Medicine, New York, NY 10010, United States of America
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT 06510, United States of America
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT 06510, United States of America; VA Connecticut Healthcare System, Veterans Aging Cohort Study, West Haven, CT 06516, United States of America
| | - Kendall J Bryant
- National Institute on Alcohol Abuse and Alcoholism HIV/AIDS Program, Bethesda, MD 20892-7003, United States of America
| | - David A Fiellin
- Yale School of Medicine, New Haven, CT 06510, United States of America; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT 06510, United States of America
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Torabi SJ, Benchetrit L, Kuo Yu P, Cheraghlou S, Savoca EL, Tate JP, Judson BL. Prognostic Case Volume Thresholds in Patients With Head and Neck Squamous Cell Carcinoma. JAMA Otolaryngol Head Neck Surg 2019; 145:708-715. [PMID: 31194229 PMCID: PMC6567848 DOI: 10.1001/jamaoto.2019.1187] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 04/11/2019] [Indexed: 01/14/2023]
Abstract
IMPORTANCE Though described as an important prognostic indicator, facility case volume thresholds for patients with head and neck squamous cell carcinoma (HNSCC) have not been previously developed to date. OBJECTIVE To identify prognostic case volume thresholds of facilities that manage HNSCC. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of 351 052 HNSCC cases reported from January 1, 2004, through December 31, 2014, by Commission of Cancer-accredited cancer centers from the US National Cancer Database. Data were analyzed from August 1, 2018, to April 5, 2019. EXPOSURES Treatment of HNSCC at facilities with varying case volumes. MAIN OUTCOMES AND MEASURES Using all-cause mortality outcomes among adult patients with HNSCC, 10 groups with increasing facility case volume were created and thresholds were identified where group survival differed compared with each of the 2 preceding groups (univariate log-rank analysis). Groups were collapsed at these thresholds and the prognostic value was confirmed using multivariable Cox regression. Prognostic meaning of these thresholds was assessed in subgroups by category (localized [I/II] and advanced [III/IV]), without metastasis (M0), with metastasis (M1), and anatomic subsites (nonoropharyngeal HNSCC and oropharyngeal HNSCC with known human papillomavirus status). RESULTS Of 250 229 eligible patients treated at 1229 facilities in the United States, there were 185 316 (74.1%) men and 64 913 (25.9%) women and the mean (SD) age was 62.8 (12.1) years. Three case volume thresholds were identified (low: ≤54 cases per year; moderate: >54 to ≤165 cases per year; and high: >165 cases per year). Compared with the moderate-volume group, multivariate analysis found that treatment at low-volume facilities (LVFs) was associated with a higher risk of mortality (hazard ratio [HR], 1.09; 99% CI, 1.07-1.11), whereas treatment at high-volume facilities (HVFs) was associated with a lower risk of mortality (HR, 0.92; 99% CI, 0.89-0.94). Subgroup analysis with Bonferroni correction revealed that only the moderate- vs low- threshold had meaningful differences in outcomes in localized stage (I/II) cancers, (LVFs vs moderate-volume facilities [MVFs]: HR, 1.09 [99% CI, 1.05-1.13]; HVF vs MVF: HR, 0.95 [99% CI, 0.90-1.00]), whereas both thresholds were meaningful in advanced stage (III/IV) cancers (LVF vs MVF: HR, 1.09 [99% CI, 1.06-1.12]; HVF vs MVF: HR, 0.91 [99% CI, 0.88-0.94]). Survival differed by prognostic thresholds for both M0 (LVF vs MVF: HR, 1.09 [99% CI, 1.07-1.12]; HVF vs MVF: HR, 0.91 [99% CI, 0.89-0.94]) and nonoropharyngeal HNSCC (LVF vs MVF: HR, 1.10 [99% CI, 1.07-1.13]; HVF vs MVF: HR, 0.93 [99% CI, 0.90-0.97]) site cases, but not for M1 (LVF vs MVF: HR, 1.00 [99% CI, 0.92-1.09]; HVF vs MVF: HR, 0.94 [99% CI, 0.83-1.07]) or oropharyngeal HNSCC cases (when controlling for human papillomavirus status) (LVF vs MVF: HR, 1.10 [99% CI, 0.99-1.23]; HVF vs MVF: HR, 1.07 [99% CI, 0.94-1.22]). CONCLUSIONS AND RELEVANCE Higher volume facility threshold results appear to be associated with increases in survival rates for patients treated for HNSCC at MVFs or HVFs compared with LVFs, which suggests that these thresholds may be used as quality markers.
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Affiliation(s)
- Sina J. Torabi
- Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
| | - Liliya Benchetrit
- Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
| | - Phoebe Kuo Yu
- Department of Otolaryngology, Harvard University School of Medicine, Boston, Massachusetts
| | - Shayan Cheraghlou
- Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
| | - Emily L. Savoca
- Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
| | - Janet P. Tate
- Department of Internal Medicine, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare System, West Haven
| | - Benjamin L. Judson
- Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
- Yale Cancer Center, New Haven, Connecticut
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McKellar MS, Kuchibhatla MN, Oursler KAK, Crystal S, Akgün KM, Crothers K, Gibert CL, Nieves-Lugo K, Womack J, Tate JP, Fillenbaum GG. Racial Differences in Change in Physical Functioning in Older Male Veterans with HIV. AIDS Res Hum Retroviruses 2019; 35:1034-1043. [PMID: 30963773 DOI: 10.1089/aid.2018.0296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Little is known about longitudinal change in physical functioning of older African American/Black and White HIV-infected persons. We examined up to 10 years of data on African American (N = 1,157) and White (N = 400) men with HIV infection and comparable HIV-negative men (n = 1,137 and 530, respectively), age 50-91 years from the Veterans Aging Cohort Study Survey sample. Physical functioning was assessed using the SF-12 (12-Item Short Form Health Survey) physical component summary (PCS) score. Mixed-effects models examined association of demographics, health conditions, health behaviors, and selected interactions with PCS score; HIV biomarkers were evaluated for HIV-infected persons. PCS scores were approximately one standard deviation below that of the general U.S. population of similar age. Across the four HIV/race groups, over time and through ages 65-75 years, PCS scores were maintained; differences were not clinically significant. PCS score was not associated with race or with interactions among age, race, and HIV status. CD4 and viral load counts of African American and White HIV-infected men were similar. Older age, low socioeconomic status, chronic health conditions and depression, lower body mass index, and smoking were associated with poorer PCS score in both groups. Exercising and, counterintuitively, being HIV infected were associated with better PCS score. Among these older African American and White male veterans, neither race nor HIV status was associated with PCS score, which remained relatively stable over time. Chronic disease, depression, and lack of exercise were associated with lower PCS score. To maintain independence in this population, attention should be paid to controlling chronic conditions, and emphasizing good health behaviors.
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Affiliation(s)
- Mehri S. McKellar
- Division of Infectious Diseases, Department of Medicine, Duke University, Durham, North Carolina
| | | | - Kris Ann K. Oursler
- Department of Internal Medicine, Salem Veterans Affairs Medical Center, Salem, Virginia
- Department of Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia
| | - Stephen Crystal
- Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, New Jersey
| | - Kathleen M. Akgün
- Department of Internal Medicine, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Kristina Crothers
- Department of Medicine, University of Washington School of Medicine, Seattle, Washington
| | - Cynthia L. Gibert
- Washington DC Veterans Affairs Medical Center, Washington, District of Columbia
- George Washington University School of Medicine and Health Sciences, Washington, District of Columbia
| | - Karen Nieves-Lugo
- Department of Psychology, George Washington University, Washington, District of Columbia
| | - Julie Womack
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
- Yale School of Nursing, New Haven, Connecticut
| | - Janet P. Tate
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
- Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut
| | - Gerda G. Fillenbaum
- Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, North Carolina
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Edelman EJ, Maisto SA, Hansen NB, Cutter CJ, Dziura J, Deng Y, Fiellin LE, O'Connor PG, Bedimo R, Gibert CL, Marconi VC, Rimland D, Rodriguez-Barradas MC, Simberkoff MS, Tate JP, Justice AC, Bryant KJ, Fiellin DA. Integrated stepped alcohol treatment for patients with HIV and alcohol use disorder: a randomised controlled trial. Lancet HIV 2019; 6:e509-e517. [PMID: 31109915 DOI: 10.1016/s2352-3018(19)30076-1] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 02/21/2019] [Accepted: 03/05/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND We examined the effectiveness of integrated stepped alcohol treatment (ISAT) on alcohol use and HIV outcomes among patients living with HIV and alcohol use disorder. METHODS In this multisite, randomised controlled trial, conducted in five Veterans Affairs-based HIV clinics in the USA (Atlanta, GA; Brooklyn-Manhattan, NY; Dallas and Houston, TX; and Washington, DC), we recruited people living with HIV and an alcohol use disorder who were not otherwise receiving formal alcohol treatment. Patients were eligible if they were aged 18 years or older, HIV positive, English speaking, and met criteria for alcohol use disorder by the Diagnostic and Statistical Manual for Mental Disorders-IV criteria for alcohol abuse or dependence. Key exclusion criteria included if the patient was acutely suicidal or had a psychiatric condition that affected their ability to participate in counselling interventions, or if they had any medical conditions that would preclude completing the study or cause harm during the course of the study. Using a web-based clinical trial management system, we randomly assigned participants (1:1) to receive ISAT or treatment as usual; patients, investigators, and clinicians were unmasked to allocation. ISAT involved three steps: step 1, addiction physician management, comprising eight sessions; step 2, addiction physician management plus motivational enhancement therapy, comprising four sessions; and step 3, specialty referral. Participants were stepped up at weeks 4 and 12 if they exceeded a priori drinking criteria. Treatment as usual involved referral to substance use treatment services. The primary outcome was number of drinks per week over the past 30 days at week 24 by use of the timeline followback method, assessed in the intention-to-treat population. Adverse events were tracked throughout the study period in all randomly assigned participants. This trial is registered at ClinicalTrials.gov, number NCT01410123. FINDINGS Between Jan 28, 2013, and July 14, 2017, 128 of 351 patients assessed for eligibility were eligible and randomly assigned to receive ISAT (n=63) or treatment as usual (n=65). Mean age was 54 years (range 23-70), 125 (98%) of 128 participants were men, and 101 (79%) were black. 25 (20%) were lost to follow-up. In the ISAT group, of 57 participants who did not die or withdraw, 30 (52%) advanced to step 2, and 17 (57%) of 30 advanced to step 3. 32 (51%) of 63 participants assigned to ISAT versus 17 (26%) of 65 assigned to treatment as usual received at least one alcohol treatment medication (p=0·004). Participants in both groups decreased their alcohol consumption, but at week 24 we did not detect a difference in number of drinks per week between the groups (least squares mean 10·4 drinks per week [SD 16·5] in the ISAT group vs 15·6 drinks per week [SD 17·6] in the treatment as usual group; adjusted mean difference -4·2, 95% CI -9·4 to 0·9; p=0·11). One adverse event occurred that was possibly related to treatment occurred in the ISAT group (headache). INTERPRETATION ISAT increases the receipt of alcohol treatment medications and counselling without changes in drinking at week 24. Strategies to implement and enhance ISAT are needed. Future efforts should focus on promoting ISAT with attention to enhancing patient engagement and retention in alcohol-related care. FUNDING US National Institute on Alcohol Abuse and Alcoholism.
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Affiliation(s)
- E Jennifer Edelman
- Yale School of Medicine, New Haven, CT, USA; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA.
| | | | - Nathan B Hansen
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA; College of Public Health, University of Georgia, Athens, GA, USA
| | | | - James Dziura
- Yale School of Medicine, New Haven, CT, USA; Yale Center for Analytic Sciences, Yale University School of Public Health, New Haven, CT, USA
| | - Yanhong Deng
- Yale Center for Analytic Sciences, Yale University School of Public Health, New Haven, CT, USA
| | - Lynn E Fiellin
- Yale School of Medicine, New Haven, CT, USA; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | | | - Roger Bedimo
- Veterans Affairs North Texas Health Care System and UT Southwestern, Dallas, TX, USA
| | - Cynthia L Gibert
- Washington DC Veterans Affairs Medical Center and George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - Vincent C Marconi
- Atlanta Veterans Affairs Medical Center and Emory University School of Medicine, Atlanta, GA, USA
| | - David Rimland
- Atlanta Veterans Affairs Medical Center and Emory University School of Medicine, Atlanta, GA, USA
| | | | - Michael S Simberkoff
- Veterans Affairs NY Harbor Healthcare System and New York University School of Medicine, New York, NY, USA
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT, USA; Veterans Affairs Connecticut Healthcare System, Veterans Aging Cohort Study, West Haven, CT, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, USA; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA; Veterans Affairs Connecticut Healthcare System, Veterans Aging Cohort Study, West Haven, CT, USA
| | - Kendall J Bryant
- National Institute on Alcohol Abuse and Alcoholism HIV/AIDS Program, Bethesda, MD, USA
| | - David A Fiellin
- Yale School of Medicine, New Haven, CT, USA; Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
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Kranzler HR, Zhou H, Kember RL, Smith RV, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Author Correction: Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 2019; 10:2275. [PMID: 31101824 PMCID: PMC6525240 DOI: 10.1038/s41467-019-10254-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The original version of this Article omitted the following from the Acknowledgements: 'Supported by the Mental Illness Research, Education and Clinical Center of the Veterans Integrated Service Network 4 of the Department of Veterans Affairs.' This has now been corrected in both the PDF and HTML versions of the Article.
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Affiliation(s)
- Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. .,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.
| | - Hang Zhou
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Rachel L Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Rachel Vickers Smith
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.,University of Louisville School of Nursing, Louisville, KY, 40202, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA.,Yale School of Public Health, New Haven, CT, 06511, USA
| | - Scott Damrauer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.,Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA.,Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Derek Klarin
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Jeffrey Reid
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - John Overton
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Daniel J Rader
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Zhongshan Cheng
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - William C Becker
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - John Concato
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Ke Xu
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Renato Polimanti
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Hongyu Zhao
- Yale School of Medicine, New Haven, CT, 06511, USA.,Yale School of Public Health, New Haven, CT, 06511, USA
| | - Joel Gelernter
- Yale School of Medicine, New Haven, CT, 06511, USA.,Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
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Benchetrit L, Torabi SJ, Tate JP, Mehra S, Osborn HA, Young MR, Burtness B, Judson BL. Gender disparities in head and neck cancer chemotherapy clinical trials participation and treatment. Oral Oncol 2019; 94:32-40. [PMID: 31178210 DOI: 10.1016/j.oraloncology.2019.05.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 04/30/2019] [Accepted: 05/09/2019] [Indexed: 01/10/2023]
Abstract
OBJECTIVES To characterize the representation of women in clinical trials directing the National Comprehensive Cancer Network (NCCN) guidelines for chemotherapy use in head and neck squamous cell carcinoma (HNSCC), as well as the relationship between gender and chemotherapy administration in the definitive treatment of HNSCC in the United States. METHODS A review of all HNSCC chemotherapy clinical trials cited by the 2018 NCCN guidelines was performed. Sex-based proportions were compared with the corresponding proportions in the general U.S. population of patients with HNSCC between 1985 and 2015, derived from the Surveillance, Epidemiology, and End Results (SEER) program. A second analysis using the National Cancer Database (NCDB), identified 63,544 adult patients diagnosed with stages III-IVB HNSCC between 2004 and 2014 and treated with definitive radiotherapy or chemoradiotherapy. Univariable and multivariable logistic regression analyses were used to identify predictors of chemotherapy administration. RESULTS While women comprised 26.2% of U.S. patients with HNSCC between 1985 and 2015, they comprised only 17.0% of patients analyzed in U.S. NCCN-cited chemotherapy clinical trials between 1985 and 2017. On multivariable analysis, women had decreased odds of receiving chemotherapy (Odds Ratio [OR]: 0.875; 95% Confidence Interval [CI]: 0.821-0.931; p < 0.001). CONCLUSION Women are underrepresented in HNSCC chemotherapy clinical trials cited by the national guidelines. Additionally, women are less likely than men to receive definitive chemoradiotherapy as oppose to definitive radiotherapy. Reasons for these disparities warrant further investigation as well as re-evaluation of eligibility criteria and enrollment strategies, in order to improve relevance of clinical trials to women with HNSCC.
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Affiliation(s)
- Liliya Benchetrit
- Department of Surgery, Section of Otolaryngology, Yale University School of Medicine, New Haven, CT, United States
| | - Sina J Torabi
- Department of Surgery, Section of Otolaryngology, Yale University School of Medicine, New Haven, CT, United States
| | - Janet P Tate
- Department of Internal Medicine, Veterans Affairs Connecticut Healthcare System, West Haven, CT, United States
| | - Saral Mehra
- Department of Surgery, Section of Otolaryngology, Yale University School of Medicine, New Haven, CT, United States; Yale Cancer Center, New Haven, CT, United States
| | - Heather A Osborn
- Department of Surgery, Section of Otolaryngology, Yale University School of Medicine, New Haven, CT, United States; Yale Cancer Center, New Haven, CT, United States
| | - Melissa R Young
- Yale Cancer Center, New Haven, CT, United States; Department of Therapeutic Radiology, Yale School of Medicine, New Haven, CT, United States
| | - Barbara Burtness
- Yale Cancer Center, New Haven, CT, United States; Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, United States
| | - Benjamin L Judson
- Department of Surgery, Section of Otolaryngology, Yale University School of Medicine, New Haven, CT, United States; Yale Cancer Center, New Haven, CT, United States.
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48
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Kranzler HR, Zhou H, Kember RL, Vickers Smith R, Justice AC, Damrauer S, Tsao PS, Klarin D, Baras A, Reid J, Overton J, Rader DJ, Cheng Z, Tate JP, Becker WC, Concato J, Xu K, Polimanti R, Zhao H, Gelernter J. Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations. Nat Commun 2019; 10:1499. [PMID: 30940813 PMCID: PMC6445072 DOI: 10.1038/s41467-019-09480-8] [Citation(s) in RCA: 259] [Impact Index Per Article: 51.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 03/06/2019] [Indexed: 12/21/2022] Open
Abstract
Alcohol consumption level and alcohol use disorder (AUD) diagnosis are moderately heritable traits. We conduct genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores and AUD diagnoses in a multi-ancestry Million Veteran Program sample (N = 274,424). We identify 18 genome-wide significant loci: 5 associated with both traits, 8 associated with AUDIT-C only, and 5 associated with AUD diagnosis only. Polygenic Risk Scores (PRS) for both traits are associated with alcohol-related disorders in two independent samples. Although a significant genetic correlation reflects the overlap between the traits, genetic correlations for 188 non-alcohol-related traits differ significantly for the two traits, as do the phenotypes associated with the traits' PRS. Cell type group partitioning heritability enrichment analyses also differentiate the two traits. We conclude that, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.
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Affiliation(s)
- Henry R Kranzler
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA.
| | - Hang Zhou
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Rachel L Kember
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Rachel Vickers Smith
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
- University of Louisville School of Nursing, Louisville, KY, 40202, USA
| | - Amy C Justice
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
- Yale School of Public Health, New Haven, CT, 06511, USA
| | - Scott Damrauer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Crescenz Veterans Affairs Medical Center, Philadelphia, PA, 19104, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, 94304, USA
- Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Derek Klarin
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Jeffrey Reid
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - John Overton
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Daniel J Rader
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Zhongshan Cheng
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Janet P Tate
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - William C Becker
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - John Concato
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Ke Xu
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Renato Polimanti
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Hongyu Zhao
- Yale School of Medicine, New Haven, CT, 06511, USA
- Yale School of Public Health, New Haven, CT, 06511, USA
| | - Joel Gelernter
- Yale School of Medicine, New Haven, CT, 06511, USA
- Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
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49
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Edelman EJ, Gordon KS, Crothers K, Akgün K, Bryant KJ, Becker WC, Gaither JR, Gibert CL, Gordon AJ, Marshall BDL, Rodriguez-Barradas MC, Samet JH, Justice AC, Tate JP, Fiellin DA. Association of Prescribed Opioids With Increased Risk of Community-Acquired Pneumonia Among Patients With and Without HIV. JAMA Intern Med 2019; 179:297-304. [PMID: 30615036 PMCID: PMC6439696 DOI: 10.1001/jamainternmed.2018.6101] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
IMPORTANCE Some opioids are known immunosuppressants; however, the association of prescribed opioids with clinically relevant immune-related outcomes is understudied, especially among people living with HIV. OBJECTIVE To assess the association of prescribed opioids with community-acquired pneumonia (CAP) by opioid properties and HIV status. DESIGN, SETTING, AND PARTICIPANTS This nested case-control study used data from patients in the Veterans Aging Cohort Study (VACS) from January 1, 2000, through December 31, 2012. Participants in VACS included patients living with and without HIV who received care in Veterans Health Administration (VA) medical centers across the United States. Patients with CAP requiring hospitalization (n = 4246) were matched 1:5 with control individuals without CAP (n = 21 146) by age, sex, race/ethnicity, length of observation, and HIV status. Data were analyzed from March 15, 2017, through August 8, 2018. EXPOSURES Prescribed opioid exposure during the 12 months before the index date was characterized by a composite variable based on timing (none, past, or current); low (<20 mg), medium (20-50 mg), or high (>50 mg) median morphine equivalent daily dose; and opioid immunosuppressive properties (yes vs unknown or no). MAIN OUTCOME AND MEASURE CAP requiring hospitalization based on VA and Centers for Medicare & Medicaid data. RESULTS Among the 25 392 VACS participants (98.9% male; mean [SD] age, 55 [10] years), current medium doses of opioids with unknown or no immunosuppressive properties (adjusted odds ratio [AOR], 1.35; 95% CI, 1.13-1.62) and immunosuppressive properties (AOR, 2.07; 95% CI, 1.50-2.86) and current high doses of opioids with unknown or no immunosuppressive properties (AOR, 2.07; 95% CI, 1.50-2.86) and immunosuppressive properties (AOR, 3.18; 95% CI, 2.44-4.14) were associated with the greatest CAP risk compared with no prescribed opioids or any past prescribed opioid with no immunosuppressive (AOR, 1.24; 95% CI, 1.09-1.40) and immunosuppressive properties (AOR, 1.42; 95% CI, 1.21-1.67), especially with current receipt of immunosuppressive opioids. In stratified analyses, CAP risk was consistently greater among people living with HIV with current prescribed opioids, especially when prescribed immunosuppressive opioids (eg, AORs for current immunosuppressive opioids with medium dose, 1.76 [95% CI, 1.20-2.57] vs 2.33 [95% CI, 1.60-3.40]). CONCLUSIONS AND RELEVANCE Prescribed opioids, especially higher-dose and immunosuppressive opioids, are associated with increased CAP risk among persons with and without HIV.
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Affiliation(s)
- E Jennifer Edelman
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, Connecticut
| | - Kirsha S Gordon
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Veterans Affairs Connecticut Healthcare System, West Haven
| | | | - Kathleen Akgün
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Veterans Affairs Connecticut Healthcare System, West Haven
| | - Kendall J Bryant
- HIV/AIDS Program, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland
| | - William C Becker
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Veterans Affairs Connecticut Healthcare System, West Haven
| | - Julie R Gaither
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Cynthia L Gibert
- DC Veterans Affairs Medical Center, Washington, DC.,Department of Medicine, George Washington University, Washington, DC
| | - Adam J Gordon
- Salt Lake City Veterans Affairs Medical Center, Salt Lake City, Utah.,Department of Medicine, University of Utah, Salt Lake City
| | - Brandon D L Marshall
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
| | | | - Jeffrey H Samet
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts.,Department of Community Health Sciences, Boston University School of Public Health, Boston, Massachusetts
| | - Amy C Justice
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, Connecticut.,Veterans Affairs Connecticut Healthcare System, West Haven
| | - Janet P Tate
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Veterans Affairs Connecticut Healthcare System, West Haven
| | - David A Fiellin
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut.,Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, Connecticut
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50
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Vickers Smith R, Kranzler HR, Justice AC, Tate JP. Longitudinal Drinking Patterns and Their Clinical Correlates in Million Veteran Program Participants. Alcohol Clin Exp Res 2019; 43:465-472. [PMID: 30592535 DOI: 10.1111/acer.13951] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Accepted: 12/19/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND A variety of measures have been developed to screen for hazardous or harmful drinking. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is one of the screening measures recommended by the U.S. Preventive Services Task Force. Annual administration of the AUDIT-C to all primary care patients is required by the U.S. Veterans Affairs Health System. The availability of data from the repeated administration of this instrument over time in a large patient population provides an opportunity to evaluate the utility of the AUDIT-C for identifying distinct drinking groups. METHODS Using data from the Million Veteran Program cohort, we modeled group-based drinking trajectories using 2,833,189 AUDIT-C scores from 495,178 Veterans across an average 6-year time period. We also calculated patients' age-adjusted mean AUDIT-C scores to compare to the drinking trajectories. Finally, we extracted data on selected clinical diagnoses from the electronic health record and assessed their associations with the drinking trajectories. RESULTS Of the trajectory models, the 4-group model demonstrated the best fit to the data. AUDIT-C trajectories were highly correlated with the age-adjusted mean AUDIT-C scores (rs = 0.94). Those with an alcohol use disorder diagnosis had 10 times the odds of being in the highest trajectory group (consistently hazardous/harmful) compared to the lowest drinking trajectory group (infrequent). Those with hepatitis C, posttraumatic stress disorder, liver cirrhosis, and delirium had 10, 7, 21, and 34%, respectively, higher odds of being classified in the highest drinking trajectory group versus the lowest drinking trajectory group. CONCLUSIONS Trajectories and age-adjusted mean scores are potentially useful approaches to optimize the information provided by the AUDIT-C. In contrast to trajectories, age-adjusted mean AUDIT-C scores also have clinical relevance for real-time identification of individuals for whom an intervention may be warranted.
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Affiliation(s)
- Rachel Vickers Smith
- University of Louisville School of Nursing , Louisville, Kentucky.,Mental Illness Research, Education and Clinical Center , Crescenz VAMC, Philadelphia, Pennsylvania
| | - Henry R Kranzler
- Mental Illness Research, Education and Clinical Center , Crescenz VAMC, Philadelphia, Pennsylvania.,Department of Psychiatry, Center for Studies of Addiction, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Amy C Justice
- VA Connecticut Healthcare System , West Haven, Connecticut.,School of Medicine , Yale University, New Haven, Connecticut
| | - Janet P Tate
- VA Connecticut Healthcare System , West Haven, Connecticut.,School of Medicine , Yale University, New Haven, Connecticut
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